Systems and methods for dynamically educating users on sports terminology

Systems and methods are described for a media guidance application (e.g., implemented on a user device) that explains sports terminology to a user accessing content that corresponds to a sporting event. The media guidance application may detect terms used in the content, determine the terms are unique to the sport, and display definitions and explanations alongside the terms.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a national stage application under 35 U.S.C. § 371 of International Application PCT/US2017/061055, filed Nov. 10, 2017, which is hereby incorporated by reference herein in its entirety.

BACKGROUND

The amount of media available to users in any given media delivery system can be substantial. Unfortunately, users unfamiliar with the media can be exposed to large amounts of information which may be difficult to comprehend. In particular, media associated with sports can feature technical terms and colloquial phrases that can alienate a user and prevent him/her from enjoying the content, or understanding the sport. Conventional media systems may define technical terms in a media asset, but they do not consider the education level or previous exposure to the media asset the user may have. As a result, conventional media systems may make inefficient use of resources, only to inundate the user with irrelevant information, making the media asset less enjoyable.

SUMMARY

Systems and methods are described to explain sports terminology to a user accessing content corresponding to a sporting event, based on his/her knowledge of the sport. For example, suppose that the user is watching a baseball game and a player in the game has hit a homerun. The media guidance application may determine that the user has never watched a baseball game and does not know much about baseball. As a result, the media guidance application may identify words that are either mentioned by the sports commentators, in closed-captioning, or on the display, such as “homerun,” and define the words for the user. The media guidance application may generate for display, an overlay, that is presented to the user, with an explanation of the term. If the user accesses additional content corresponding to baseball in the future, the media guidance application may detect that the user has already been provided explanations of various terms such as “homerun,” and either present a more advanced explanation of terms, or no explanation.

The media guidance application may detect that a user is currently accessing content corresponding to a sporting event of a given type. Suppose that the user is viewing a baseball game on his/her set-top box. It should be noted that the user may access on sporting event across various mediums such as on-demand content (e.g., VOD), Internet content (e.g., streaming media, downloadable media, etc.), locally stored content (e.g., content stored on any user equipment device described above or other storage device), or other time-independent content. The media guidance application may extract metadata associated with the baseball game, such as the name and the description of the content, to search for references to a sport. The media guidance application may specifically determine that the name of a sport (e.g., baseball) is found in the name or description of the content. Accordingly, the media guidance application may determine that the content is associated with the identified sporting event.

The media guidance application may determine a frequency representing how often the user views sporting events of the given type to establish an education level of the user associated with the given type of sporting event. For example, the media guidance application may refer to the viewing history of the user to identify media assets the user has previously viewed that correspond to the sporting event type. Suppose that the media guidance application identifies several media assets that the user previously accessed that correspond to baseball. The media guidance application may determine the time of access for each media asset and determine a frequency value (e.g., accessed one per week, twice a month, etc.) based on the number of times the user accessed the media assets in a given period of time. Based on the frequency value, the media guidance application may use a lookup table to determine an education level of the user in terms of the sport. For example, the media guidance application may determine that frequency of one time per day (e.g., the user views content associated with baseball on daily basis) indicates that the user has an “advanced” understanding of baseball. Therefore, the education level of the user may be “advanced” for baseball-related content. Alternatively, the media guidance application may determine that the user views baseball-related content with a frequency of once a week. Accordingly, the media guidance application may determine, using the lookup table, that the user's education level is “intermediate.”

The media guidance application may then detect a term unique to the given type of sporting event in the content. The media guidance application may actively monitor for terms by analyzing any closed-captioning data associated with the content, sports commentary audio, or visual cues such as an in-game overlay of metrics when a player comes to bat. The media guidance application may utilize computer vision to process visual information, and natural language processing to identify words. For example, the user may be viewing a baseball game and the sports commentator may use the term “slugging percentage.” The media guidance application may first identify the term using the processes mentioned, and then use a lookup table to determine that the term is unique to the sporting event type, baseball.

In response to determining that the education level of the user is less than a threshold, the media guidance application may present an explanation of the term to the user while the user accesses the content. The threshold may be a value associated with the identified term. For example, the lookup table that indicates whether the term is unique to the sporting event type may also provide a definition of the term and a threshold that represents the maximum education level that requires an explanation of the term. Suppose that the user's education level is “advanced” and the threshold is “expert,” a value greater than the user's education level. In response to determining that the user's education level is lower than the threshold, the media guidance application may determine that the term “slugging percentage” should be provided and may generate, for display, an explanation to the user as he/she views the content.

In some aspects, the media guidance application may detect that a user is currently accessing content corresponding to a sporting event of a given type. In some embodiments, the content includes at least one of a linear media asset (e.g., television broadcast of a sports event), an on-demand media asset (e.g., a recording of a sports documentary), and social chatter on a social platform associated with the user (e.g., sports forum or discussion). Suppose that the user is accessing a baseball game on the television channel, FOX, on his/her set-top box. The media guidance application may retrieve channel metadata associated with FOX to determine what the user is viewing. Channel metadata, as generated by the content provider, may include information such as the media listings of the channel (e.g., the names of the television shows/movies broadcasted), respective content descriptions, and the content schedule (e.g., time stamps for each television show or movie). In this case, the media guidance application may determine that the name of the content the user is currently watching is “MLB Baseball: New York Yankees vs. Boston Red Sox,” which has a description listed as “Major League Baseball season game between the New York Yankees and the Boston Red Sox.” The media guidance application may retrieve or access a sports database that lists a variety of sports (e.g., baseball, basketball, tennis, etc.). The media guidance application may then search the name of the content, and/or the description, for a sport listed in the sports database. For example, the media guidance application may retrieve the term “baseball” from the sports database, search for “baseball” in the strings of the name and/or description, and determine that “baseball” is found in the string(s) (e.g., in the name of the content or in the description). Therefore, the media guidance application may detect that the user is currently accessing content corresponding to the sporting event type, baseball.

The media guidance application may search, based on the given type of the sporting event, a viewing history associated with the user to identify a plurality of media assets corresponding to sporting events of the given type. For example, the media guidance application may retrieve a user profile associated with the user that provides information such as the user's viewing history, content preferences, bookmarks, etc. The media guidance application may access the viewing history of the user to determine the media assets the user has viewed that correspond to the sport event type detected. For example, the media guidance application may search for the term “baseball” in the metadata of the media assets (e.g., name, description) found in the viewing history. Suppose that the user has rarely watched baseball. The media guidance application may determine that the viewing history only has three instances of media assets corresponding to baseball.

The media guidance application may retrieve a viewing time associated with each of the plurality of media assets. For example, the viewing history may also list time stamps of the times the user viewed the media assets. Consider the three media assets corresponding to baseball: game 1, game 2, and game 3. The media guidance application may determine the viewing times, based on the metadata of the media assets, as Oct. 2, 2015 at 5:00 pm, Oct. 2, 2016 at 6:00 pm, and Oct. 2, 2017 at 5:30 pm, respectively. In this case, game 3 may be the currently accessed content.

The media guidance application may compare an average of differences between the viewing times associated with each of the plurality of media assets. For example, the media guidance application may first determine the difference between the three media assets mentioned previously. The difference between the viewing time of game 1 and game 2 is one year and the difference between game 2 and game 3 is one year. Therefore, the media guidance application may determine that the average of differences between media assets is one year.

The media guidance application may determine, based on the computed average, a frequency representing how often the user views sporting events of the given type. The frequency may be a quantitative (e.g., 5 times per week, 10 times per month, etc.) or a qualitative value (e.g., often, very often, rarely, etc.). For example, the media guidance application may determine that the average difference between the media asset viewing times is one year. Therefore, the user watches media assets corresponding to baseball once a year. If the media guidance application relies on a qualitative frequency, the media guidance application may determine classifications of various numerical values. For example, the frequency 1 times per week may be classified as “not often,” 3 times per week may be classified as “average,” 5 times per week may be classified as “often,” etc. In this case, the media guidance application may determine the frequency to be 1/52 times per week, which the media guidance application may classify as “rarely.” The user may select whether the media guidance application should use qualitative values or quantitative values.

The media guidance application may search a database of education levels to identify a first education level associated with the determined frequency to establish a first sport education level of the user associated with the given type of sporting event. The first sport education level may represent the level of knowledge a user has about a specific sport, and is used to determine whether certain terms should be explained to the user and how complicated the explanations can be. The database of education levels may be a lookup table (e.g., array of strings) that lists education levels (e.g., some high school, high school diploma, some college, associate degree, bachelor degree, etc.) in separate rows and the frequency (e.g., rarely, average, often, etc.) in separate columns. The intersection of an education level and the frequency may indicate the first sport education level (e.g., completely new, beginner, intermediate, advanced, expert, etc.). For example, the intersection of “bachelor degree” and “often” may indicate that the user has an “advanced” first sport education level. The media guidance application may determine the first education level of the user by requesting user input of the education level, or referring to social media (e.g., education field of user's Facebook profile). In some embodiments, the media guidance application may receive user input setting a value for the education level of the user as the first education level. Suppose that the user indicates that his/her first education level is “high school diploma.” The frequency, as determined by the media guidance application, is “rarely.” The media guidance application may use these inputs to lookup the user's first sport education level. Based on the database of education levels, the media guidance application may determine that the user has a “beginner” first sport education level.

The media guidance application may process metadata associated with the currently accessed content to identify a plurality of terms describing the sporting event type. In some embodiments, processing the metadata associated with the currently accessed content comprises receiving closed-captioning information corresponding to the currently accessed content. For example, the media guidance application may determine that closed-captioning is available in the currently accessed content. The media guidance application may extract the closed-captioning data and identify words associated with the sporting event type. In the case that closed-captioning is not available, the media guidance application may also convert speech (e.g., sports commentary) in the currently accessed content to text using natural language processing (e.g., speech recognition).

In some embodiments, processing the metadata associated with the currently accessed content comprises processing visual information presented in the content to detect metrics of the sporting event type. For example, the media guidance application may utilize computer vision processes (e.g., segmentation, edge detection, classification) and natural language processing to identify visual information in the content. Suppose that a player hits a homerun in the baseball game. The word “Homerun” may appear on the screen. Furthermore, the score of the game may change accordingly. For example, the media guidance application may identify the word “Homerun” and the metrics and determine whether the word and metrics correspond to “baseball” based on the sports database.

The media guidance application may compare the identified plurality of terms with a list of terms associated with the given type of sporting event to detect a term of the plurality of terms that is unique to the given type of sporting event in the content. For example, the closed-captioning or the commentary may include a quote “and that ball is hit far—oh but it's just a foul-ball.” The media guidance application may identify each word/phrase in the quote and determine the words/phrases that correspond solely to “baseball.” The media guidance application may refer to the sports database to determine a list of terms that correspond to a sporting event. These words may include technical terms, player names, team names, events, etc. In this example, the media guidance application may determine that the sports database for the sporting event type of “baseball” includes the list of terms “ball,” “hit,” and “foul-ball.” Therefore, the words “ball,” “hit,” and “foul-ball” from the quote correspond to the sporting event type, baseball. Furthermore, the media guidance application may determine that the terms “ball” and “hit” are not exclusive to “baseball” and are found in other sections of the sports database as well (e.g., cricket, tennis, etc.). In some embodiments, the sports database may feature an additional column that indicates whether a term is unique to the sport or the term's definition is unique to the sport (e.g., to account for sports that use similar terms with different definitions). Therefore, the media guidance application may determine that the term “foul-ball” is unique to the given type of sporting event, baseball.

The media guidance application may compare the first sport education level of the user to a threshold sport education level. The threshold sport education level may be associated with the term that is unique to the sporting event type. For example, the sports database may include a column that assigns each term a threshold sporting event educational level. In terms of baseball, terms such as “foul-ball,” “homerun,” or “base-hit” may be assigned a threshold sport education level of “beginner,” whereas “slugging percentage” may be assigned “advanced.” This may be because a viewer who is just beginning to watch baseball may need some basic information to get acclimated to the sport, whereas someone who regularly watches baseball, may not need an explanation of the basic words and may prefer getting explanations about more complex aspects of the sport. Therefore, the media guidance application may determine that the first sport education level of the user is equal to the threshold sport education level.

It should be noted that the threshold sport education level may also be a quantitative value. For example, the education levels may be ranked in a 1-10 scale where 1 represents a minimum education level and 10 represents the highest education level. Similarly, the threshold level may also be ranked in a scale from 1-10. Suppose that the sporting event type education of the user is 3 and the threshold sport education level for the term “foul-ball” is 4, the media guidance application may determine that the user's first sport education level is less than the threshold sport education level.

In response to determining that the first sport education level of the user is less than or equal to the threshold sport education level, the media guidance application may present an explanation of the term to the user while the user accesses the content. For example, the media guidance application may determine that the term “foul-ball” has a threshold sport education level of “beginner,” which matches the user's first sport education level. Likewise, if the media guidance application is using quantitative representations of the education and threshold levels, the media guidance application may determine that the user's first sport education level is less than the threshold sport education level. In response, the media guidance application may retrieve a definition of the term “foul-ball” from the sports database, or from the Internet. If the media guidance application determines that the first sport education level of the user is greater than the threshold sport education level, the media guidance application may not present a definition. This is because the user may already know the definition of the term and may not wish to be inundated with definitions.

In some embodiments, presenting the explanation of the term comprises at least one of replacing a display of the term with the explanation, presenting an overlay over the content with the explanation adjacent to the term, highlighting the term in a display, and sending the explanation to a second screen device. For example, the media guidance application may highlight the term “foul-ball” in the closed-captioning and generate an overlay that defines the term. Alternatively, the user may replace the term “foul-ball” in the closed-captioning with its definition/explanation. The media guidance application may also send the explanation to a second device (e.g., phone, laptop, tablet, television, etc.) of the user, where the media guidance application on the second device generates, for display, the explanation. If the user is listening to an audio version of the sporting event type (e.g., on the radio), the media guidance application may also dictate the explanation of the term to the user. In some embodiments, the media guidance application may use speech recognition to wait for a portion of the audio when no sports commentary is taking place and dictate the explanation of the term.

In some embodiments, the media guidance application may detect that the user is accessing a second content corresponding to the sporting event type of the given type after a period of time of accessing the first content. For example, the user may access an on-demand media asset such as a sports documentary about the New York Yankees, a MLB baseball team. The media guidance application may retrieve metadata associated with the second content from the content provider and determine whether the name or description correspond to a sport in the sports database. In this case, the media guidance application may determine that the second content has metadata that references the terms “baseball” and “New York Yankees,” which are terms found in the “baseball” section of the sports database. Therefore, the media guidance application may determine that the second content corresponds to the sporting event type, baseball. Furthermore, the media guidance application may retrieve the viewing history of the user from his/her user profile to determine the viewing time of the first content. Suppose that the user accessed the first content on Oct. 2, 2017. The user may be accessing the second content on Nov. 2, 2017. Thus, the period of time between the viewing time of the first content and the viewing time of the second content is one month.

The media guidance application may determine an increase in the frequency representing how often the user views sporting events of the given type. For example, the media guidance application may determine, based on the viewing times of the first content and the second content, that the viewing time difference is one month. In comparison, the average difference previously computed by the media guidance application was one year. Therefore, the media guidance application may detect an increase in the frequency (e.g., the user is accessing content related to the sporting event type more frequently). Alternatively, the media guidance application may re-compute the average difference between viewing times. In this case, the user has viewed, based on the viewing history, game 1, game 2, game 3 (the first content), and the documentary (the second content). The re-computed average may indicate that the user views a media asset associated with the sporting event type every 0.7 years. Since previously the computed average indicated that the user views a media asset associated with the sport event type every 1 year, the media guidance application may determine that the frequency has increased.

The media guidance application may search the database of education levels to identify a second sport education level associated with the increased frequency. Suppose that qualitatively, the frequency increased from “rarely” to “occasionally.” As discussed previously, the user's education level may be “high school diploma.” As a result, the media guidance application may search the database of education levels for the sports education level that intersects at the lookup table between “high school diploma” and the frequency “occasionally.” Suppose that the intersection is the “intermediate” sports education level. The media guidance application may identify “intermediate” as the second education level. If the media guidance application is using a quantitative scale for education levels and frequency (e.g., a scale of 1-10), the media guidance application may convert “high school diploma” to a numerical value of 3. Likewise, the numerical counterpart of “occasionally” may be 5. Based on the lookup table, these values may intersect at a second sport education level of 5. In some embodiments, the media guidance application may use the numerical values as inputs in an algorithm which outputs an appropriate sport education level.

The media guidance application may then process metadata associated with the second content to identify the term detected in the first content. As mentioned previously, the media guidance application may process metadata by extracting subtitles or closed-captioning data to identify words that correspond to the sporting event type. The media guidance application may also utilize computer vision to identify metrics, terms and objects displayed in the content. Suppose that the media guidance application identifies the term “foul-ball” once again.

The media guidance application may then compare the second sport education level of the user to the threshold sport education level. Suppose that the user's second sport education level is intermediate. The threshold sport education level of the term “foul-ball” may be “beginner,” as indicated in the sports database. Similarly, the quantitative counterpart of the threshold sport education level may be 4, and the user's second sport education level may be 5. As a result, the media guidance application may determine that the second sport education level is greater than the threshold sport education level.

In response to determining that the second sport education level of the user is greater than the threshold sport education level but less than a maximum threshold sport education level, the media guidance application may present a second explanation of the term to the user that is more advanced than the first explanation. In this case the maximum threshold sport education level may be 10 (e.g., quantitatively) or “expert” (e.g., qualitatively). The maximum threshold may represent the highest value of knowledge that can be achieved by a user in terms of the sporting event type. A user that has an “expert” sport education level may not need definitions of basic terms such as “foul-ball” or “homerun.” In this example, the media guidance application may determine the user's second sport education level is greater than the threshold sport education level, but is less than a maximum threshold sport education level. The sports database may include multiple definitions/explanations for terms based on the sport education level of a user. For example, the definition for “foul-ball” presented to a user with a “beginner” sport education level may simply be “a ball that falls in a part of the field that is not considered fair.” Alternatively, the sports database may provide the definition for “foul-ball” presented to a user with an “advanced” sport education level as “a ball that settles on foul territory between home and first base or between home and third base, or while on or over foul territory, touches the person of an umpire or player, or any object foreign to the natural ground.”

In some embodiments, the media guidance application may provide the user with fun facts or trivia associated with the term. For example, the media guidance application may retrieve trivia questions and fun fact information from the Internet, or the sports database. If the media guidance application detects the term “foul-ball,” the media guidance application may present a user with a sport education level equal to the maximum threshold sport education level with sports trivia such as “Did you know? Player X has the record for hitting the most foul-balls.” In some embodiments, the media guidance application may determine that the user has a sport education level equal to the maximum threshold sport education level and request to the user to define a term for other users. For example, the media guidance application may ask the user if he/she is interested in providing an explanation or definition for a term, in order to improve the definitions in the sports database.

In some embodiments, presenting the explanation of the term to the user comprises of the media guidance application transmitting the term to a social network associated with the user. The social network may be any platform that allows users to communicate with each other by posting comments, images, videos, etc. (e.g., Facebook, Twitter, Reddit, etc.). The media guidance application may post the term detected “foul-ball” to a social network that the user is associated with, while requesting an explanation for the term. The media guidance application may then receive input from a plurality of users on the social network, each input providing a given explanation of the term. For example, three users may provide an explanation of “foul-ball.” User 1 may post “a ball that lands past a boundary of the ballpark.” User 2 may post “a ball that lands beyond the marked lines of the play field.” User 3 may post “a ball that is not in the boundary of the playing field.” The media guidance application may identify a set of the inputs from the plurality of users having explanations in common. For example, the media guidance application may identify words and their synonyms to determine similarities between the explanations posted. In this case, the media guidance application may identify a majority of the users start their explanations with “a ball that lands” and end with “the playing field.” Furthermore, the media guidance application may recognize “past” and “beyond” as synonyms. The media guidance application may then generate the explanation of the term based on the set of the inputs. For example, based on the similarities of the posted explanations, the media guidance application may construct an explanation, which combines a set of inputs that are common, such as “a ball that lands beyond a boundary of the playing field.”

In some embodiments, the media guidance application may directly select the explanation with a number of acknowledgments (e.g., likes, retweets, comments, etc.) greater than an acknowledgment threshold, as the explanation that will be displayed to users that come across the term while accessing content. For example, if user 2 received the 100 likes for an explanation that he/she gave, the media guidance application may refer to the user profile to retrieve the acknowledgment threshold (e.g., 50). In response to determining that the amount of acknowledgments the user's explanation received is greater than the acknowledgment threshold, the media guidance application may select the explanation, instead of generating a new one based on the set of inputs.

In some embodiments, the media guidance application may receive input from the user that identifies a set of experts on the social network for the given type of sporting event. For example, the media guidance application may identify other users that also use the media guidance application and have a sport education level equal to the maximum threshold sport education level. Alternatively, the media guidance application may identify individuals or companies (e.g., MLB, NBA, NHL, etc.) that are a part of the social network, and are associated with the sporting event type. For example, these individuals may be sports announcers, players, coaches, trainers, analysts, etc. Due to their direct association with the sport, the media guidance application may identify the individuals and companies as a set of experts. The media guidance application may prompt the user whether he/she wishes to confirm the experts identified by the media guidance application. If the user confirms the experts, the media guidance application may list the identified experts in an expert database. Whenever a user posts an explanation of a term on the social network, the media guidance application may cross reference the name/username of the user with the expert database to determine whether the user is an expert of the sport. Each sport may have its own section in the expert database with different experts. The media guidance application may also limit transmission of the term to the identified set of experts. For example, the media guidance application may only consider the explanations from the experts when generating an explanation for the user based on the set of inputs that are common among each explanation posted on the social network. In some cases, the media guidance application may generate a social network profile, post a query for defining the term, and only allow experts to post on the profile with potential explanations.

In some embodiments, the media guidance application may detect display of a metric of the sporting event type in the currently accessed content. For example, during a baseball game, a player may be approaching home plate to bat. As a result, the player's batting statistics may appear on the display of the user. The media guidance application may identify the metrics by using computer vision (e.g., segmentation, edge detection, classification). It should be noted that content providers (e.g., FOX, ESPN) often place metrics in the same part of the screen for each game of a sport. For example, FOX may place a scoreboard on the top left part of the screen for every MLB baseball game. The content of the scoreboard may also be placed in the same positions (e.g., team name, followed by points of the team, followed by the inning number, etc.). When utilizing computer vision to classify numbers and words, the media guidance application may refer to a presentation database that includes pixel coordinates outlining the positions of various metrics and overlays generated by a content provider for a sporting event. The media guidance application may then limit its processing to those coordinates to identify metrics with more efficiency.

In response to identifying a display of a metric (e.g., a plurality of statistics), the media guidance application may modify the metric that is displayed based on the sport education level of the user. In some embodiments, modifying the metric comprises ranking the plurality of statistics based on an importance level associated with each statistic. Revisiting the previous example, when a player's batting statistics are shown on the screen, the metrics may include “batting average,” “on-base percentage,” “slugging percentage,” and “on-base plus slugging percentage.” The media guidance application may determine the importance of each statistic by referring to the sports database. The sports database may include a section that lists metrics associated with a sport type, and organizes them based on importance. Furthermore, each metric may have a threshold sport education level associated with it. The importance of a metric may be a pre-determined value (e.g., on a scale from 1-10 or a qualitative description such as “very important”) by the sports organization associated with the sporting event type (e.g., MLB is associated with baseball). Suppose that the media guidance application ranks “batting average” as 1 (e.g., first-most important), “on-base percentage” as 2, “slugging percentage” as 3, and “on-base plus slugging percentage” as 4 (e.g., least-most important), based on the importance listed in the sports database.

In some embodiments, the media guidance application may determine the importance of a metric based on the frequency at which appears during a sporting event type. For example, the media guidance application may analyze previous media assets associated with the sporting event and count the number of references made to a specific metric. The media guidance application may then organize the list of metrics in the sports database based on the frequency of appearance of a metric.

The media guidance application may remove a first subset of the plurality of statistics being displayed that is associated with a rank greater than a first threshold rank, in response to determining that the first sport education level of the user is greater than the threshold sport education level and less than a maximum threshold sport education level. Suppose that the first threshold rank is 2, the user's first education level is 5, the threshold sport education level is 3, and the maximum threshold sport education level is 10. The media guidance application may determine that the user's first sport education level is greater than the threshold sport education level and is lower than the maximum threshold sport education level. This may mean that the user is familiar enough with the sport to understand a certain set of terms or metrics, but not perhaps the complex ones. It should be noted that the terms and metrics that appear more frequently may be marked with greater importance. Accordingly, the media guidance application may remove a first subset of the plurality of statistics that is associated with a rank lower than the first threshold rank. In this example, the media guidance application may remove “slugging percentage” and “on-base plus slugging percentage” from the display because they rank lower than the first threshold rank.

The media guidance application may also remove a second subset of the plurality of statistics being displayed that is associated with a rank lower than a second threshold rank in response to determining that the first sport education level of the user is less than the threshold sport education level, wherein the second threshold rank is greater than the first threshold rank, and wherein the second subset includes the first subset. For example, the user's sport education level may be 2 and the threshold sport education level may be 3. Therefore, the media guidance application may determine that the user's sport education level is lower than the threshold sport education level (e.g., the user is not fully familiar with the sport). The second threshold rank may be 1, a value greater than the first threshold rank. The media guidance application may therefore remove all metrics that rank below the second threshold rank. In this case, the second subset would therefore include “on-base percentage,” “slugging percentage,” and “on-base plus slugging percentage.” It should be noted that “slugging percentage” and “on-base plus slugging percentage” were part of the first subset. Thus, the second subset includes the first subset. The user may also select to view all metrics, and prevent the media guidance application from removing metrics from display.

In some embodiments, in place of the removed metrics, the media guidance application may present trivia and fun facts to the user about the metrics that are still being displayed to the user. For example, the media guidance application may replace the section displaying “on-base percentage,” “slugging percentage,” and “on-base plus slugging percentage” with an overlay with trivia about “batting average” (e.g., “Did you know: Player X currently has the highest batting average in the league”).

In some embodiments, metrics removed from the display may be sent to a second device of the user (e.g., smartphone, television, computer, etc.) by the media guidance application. The media guidance application of the second device may generate, for display, the removed metrics along with their respective explanations.

It should be noted that the systems, methods, apparatuses, and/or aspects described above may be applied to, or used in accordance with, other systems, methods, apparatuses, and/or aspects described in this disclosure.

DETAILED DESCRIPTION

Systems and methods are described to explain sports terminology to a user accessing content corresponding to a sporting event, based on his/her knowledge of the sport. For example, suppose that the user is watching a baseball game and a player in the game has hit a homerun. The media guidance application may determine that the user has never watched a baseball game and does not know much about baseball. As a result, the media guidance application may identify words that are either mentioned by the sports commentators, in closed-captioning, or on the display, such as “homerun,” and define the words for the user. The media guidance application may generate for display, an overlay, that is presented to the user, with an explanation of the term. If the user accesses additional content corresponding to baseball in the future, the media guidance application may detect that the user has already been provided explanations of various terms such as “homerun,” and either present a more advanced explanation of terms, or no explanation.

Consider a scenario in which a user is watching a baseball match featuring the New York Yankees and the Boston Red Sox on the FOX channel on his/her set top box. Furthermore, the user is unfamiliar with the sport and has not watched a baseball game before. As a result, the user may not understand the various metrics being displayed on the screen and the terms being used by the sports commentators. Suppose that the user sees one of the players from the New York Yankees, Aaron Judge, hit a homerun. The homerun may cause one of the sports commentators to say “And that is homerun by Aaron Judge. The rookie sensation has done it again.” In addition, the word “Homerun” may be displayed in closed captioning and in an arbitrary portion of the display (e.g., center of the display or top left/right corner). As a response, the media guidance application may initiate a process to identify terms that need to be explained to the user.

FIG.1is an illustrative example of a display screen100for educating a user about terminology associated with a sporting event, in accordance with some embodiments of the disclosure. Closed-captioning102represents the transcribed commentary of the sports commentators. Score overlay104provides information such as game score, metrics and events of the game. Definitions overlay106provides explanations of the terms the media guidance application determines should be defined for the user, based on the user's familiarity with the sport.

The media guidance application may first detect that a user is currently accessing content corresponding to a sporting event of a given type. The media guidance application may retrieve channel metadata associated with FOX to determine what the user is viewing. Channel metadata, as generated by the content provider, may include information such as the media listings of the channel (e.g., the names of the television shows/movies broadcasted), respective content descriptions, and the content schedule (e.g., time stamps for each television show or movie). In this case, the media guidance application may determine that the name of the content the user is currently watching is “MLB Baseball: New York Yankees vs. Boston Red Sox,” which has a description listed as “Major League Baseball season game between the New York Yankees and the Boston Red Sox.” The media guidance application may retrieve a sports database that lists a variety of sports (e.g., baseball, basketball, tennis, etc.). The media guidance application may then search the name of the content, and/or the description, for a sport listed in the sports database. For example, the media guidance application may retrieve the term “baseball” from the sports database, search for “baseball” in the strings of the name and/or description, and determine that “baseball” is found in the string(s) (e.g., in the name of the content or in the description). Therefore, the media guidance application may detect that the user is currently accessing content corresponding to the sporting event type, baseball.

The media guidance application may then search, based on the given type of the sporting event type, a viewing history associated with the user to identify a plurality of media assets corresponding to sporting events of the given type. For example, the media guidance application may retrieve a user profile associated with the user that provides information such as the user's viewing history, content preferences, bookmarks, etc. The media guidance application may access the viewing history of the user to determine the media assets the user has viewed that correspond to the sport event detected. For example, the media guidance application may search for the term “baseball” in the metadata of the media assets (e.g., name, description) found in the viewing history. Suppose that the user has rarely watched baseball. The media guidance application may determine that the viewing history only has one media asset corresponding to baseball.

In some embodiments, the media guidance application may refer to a viewing threshold to determine a sport education level. The first sport education level may represent the level of knowledge a user has about a specific sport, and is used to determine whether certain terms should be explained to the user and how complicated the explanations can be. The viewing threshold may be the number of times a user has viewed a media asset corresponding to the sporting event type. Each sport education level may have a viewing threshold. For example, the sport education level may be a qualitative value (e.g., completely new, beginner, intermediate, advanced, expert, etc.) or a quantitative value (e.g., on a scale from 1-10). The viewing threshold for a “beginner” sport education level may be 2. The viewing threshold for an “expert” sport education level may be 100. This indicates that a user who has only viewed at least 2 media assets corresponding to baseball is generally unfamiliar with the sport type and therefore has a low sport education level. In contrast, a user that has viewed at least 100 media assets corresponding to baseball is familiar with the sport type and has a higher sport education level. In this case, since the user has only viewed one media asset corresponding to baseball, the media guidance application may determine that the sport education level of the user is “completely new.”

The media guidance application may then process metadata associated with the currently accessed content to identify a plurality of terms describing the sporting event type. For example, the media guidance application may utilize closed-captioning information corresponding to the currently accessed content. For example, the media guidance application may determine that closed-captioning is available as it is displayed in closed-captioning102(FIG.1) in the currently accessed content. The media guidance application may extract the closed-captioning data and identify words associated with the sporting event type. In the case that closed-captioning is not available, the media guidance application may also convert speech (e.g., sports commentary) in the currently accessed content to text using natural language processing (e.g., speech recognition). The media guidance application may also process visual information presented in the content as score overlay104(FIG.1) to detect metrics of the sporting event type. For example, the media guidance application may utilize computer vision processes (e.g., segmentation, edge detection, classification) and natural language processing to identify visual information in the content. Suppose that a player hits a homerun in the baseball game. The word “Homerun” may appear on the screen. Furthermore, the score of the game may change accordingly. For example, the media guidance application may therefore use segmentation and classification to identify the visual “Homerun” in score overlay104and convert it into a word. The media guidance application may then search for the word in the sports database to determine whether the word and metrics correspond to “baseball.”

The media guidance application may compare the identified plurality of terms with a list of terms associated with the given type of sporting event to detect a term of the plurality of terms that is unique to the given type of sporting event in the content. As depicted inFIG.1, the closed-captioning or the commentary may include a quote “And that is a homerun by Aaron Judge! The rookie sensation has done it again!” The media guidance application may identify each word/phrase in the quote and determine the words/phrases that correspond solely to “baseball.” The media guidance application may refer to the sports database to determine a list of terms that correspond to a sporting event. These words may include technical terms, player names, team names, events, etc. In this example, the media guidance application may determine that the sports database for “baseball” includes the list of terms “homerun,” “Aaron Judge,” and “rookie.” Therefore, the words “homerun,” “Aaron Judge,” and “rookie” from the quote correspond to the sporting event type, baseball. Furthermore, the media guidance application may determine that the term “rookie” is not exclusive to “baseball” and is found in other sections of the sports database as well (e.g., basketball, football, etc.).

The media guidance application may then compare the sport education level of the user to a threshold sport education level. The threshold sport education level may be associated with the term that is unique to the sporting event type. For example, the sports database may include a column that assigns each term a threshold sporting event educational level. In terms of baseball, terms such as “homerun,” or “Aaron Judge” may be assigned a threshold sport education level of “completely new,” whereas “slugging percentage” may be assigned “advanced.” This may be because a viewer who is just beginning to watch baseball may need some basic information to get acclimated to the sport, whereas someone who regularly watches baseball, may not need an explanation of the basic words and may prefer getting explanations about more complex aspects of the sport. Therefore, the media guidance application may determine that the first sport education level of the user is equal to the threshold sport education level.

In response to determining that the first sport education level of the user is less than or equal to the threshold sport education level, the media guidance application may present an explanation of the terms to the user while the user accesses the content. For example, the media guidance application may determine that the terms “homerun” and “Aaron Judge” have a threshold sport education level of “completely new,” which matches the user's first sport education level. The media guidance application may then highlight the terms in closed-captioning102(FIG.1) and generate for display to the user, definitions overlay106(FIG.1), which includes all the identified terms and their respective definitions. In the case where a person is referenced, the media guidance application may also provide an image of the person. Depending on the sport education level of the user, the media guidance application may provide additional details about the terms. For example, if the user has an “advanced” sport education level, definitions overlay106may include statistics of Aaron Judge's performance or may include trivia about the player or term.

FIG.2shows illustrative grid of a program listings display200arranged by time and channel that also enables access to different types of content in a single display. Display200may include grid202with: (1) a column of channel/content type identifiers204, where each channel/content type identifier (which is a cell in the column) identifies a different channel or content type available; and (2) a row of time identifiers206, where each time identifier (which is a cell in the row) identifies a time block of programming. Grid202also includes cells of program listings, such as program listing208, where each listing provides the title of the program provided on the listing's associated channel and time. With a user input device, a user can select program listings by moving highlight region210. Information relating to the program listing selected by highlight region210may be provided in program information region212. Region212may include, for example, the program title, the program description, the time the program is provided (if applicable), the channel the program is on (if applicable), the program's rating, and other desired information.

Grid202may provide media guidance data for non-linear programming including on-demand listing214, recorded content listing216, and Internet content listing218. A display combining media guidance data for content from different types of content sources is sometimes referred to as a “mixed-media” display. Various permutations of the types of media guidance data that may be displayed that are different than display200may be based on user selection or guidance application definition (e.g., a display of only recorded and broadcast listings, only on-demand and broadcast listings, etc.). As illustrated, listings214,216, and218are shown as spanning the entire time block displayed in grid202to indicate that selection of these listings may provide access to a display dedicated to on-demand listings, recorded listings, or Internet listings, respectively. In some embodiments, listings for these content types may be included directly in grid202. Additional media guidance data may be displayed in response to the user selecting one of the navigational icons220. (Pressing an arrow key on a user input device may affect the display in a similar manner as selecting navigational icons220.)

Display200may also include video region222, and options region226. Video region222may allow the user to view and/or preview programs that are currently available, will be available, or were available to the user. The content of video region222may correspond to, or be independent from, one of the listings displayed in grid202. Grid displays including a video region are sometimes referred to as picture-in-guide (PIG) displays. PIG displays and their functionalities are described in greater detail in Satterfield et al. U.S. Pat. No. 6,564,378, issued May 13, 2003 and Yuen et al. U.S. Pat. No. 6,239,794, issued May 29, 2001, which are hereby incorporated by reference herein in their entireties. PIG displays may be included in other media guidance application display screens of the embodiments described herein.

Options region226may allow the user to access different types of content, media guidance application displays, and/or media guidance application features. Options region226may be part of display200(and other display screens described herein), or may be invoked by a user by selecting an on-screen option or pressing a dedicated or assignable button on a user input device. The selectable options within options region226may concern features related to program listings in grid202or may include options available from a main menu display. Features related to program listings may include searching for other air times or ways of receiving a program, recording a program, enabling series recording of a program, setting program and/or channel as a favorite, purchasing a program, or other features. Options available from a main menu display may include search options, VOD options, parental control options, Internet options, cloud-based options, device synchronization options, second screen device options, options to access various types of media guidance data displays, options to subscribe to a premium service, options to edit a user's profile, options to access a browse overlay, or other options.

Another display arrangement for providing media guidance is shown inFIG.3. Video mosaic display300includes selectable options302for content information organized based on content type, genre, and/or other organization criteria. In display300, television listings option304is selected, thus providing listings306,308,310, and312as broadcast program listings. In display300the listings may provide graphical images including cover art, still images from the content, video clip previews, live video from the content, or other types of content that indicate to a user the content being described by the media guidance data in the listing. Each of the graphical listings may also be accompanied by text to provide further information about the content associated with the listing. For example, listing308may include more than one portion, including media portion314and text portion316. Media portion314and/or text portion316may be selectable to view content in full-screen or to view information related to the content displayed in media portion314(e.g., to view listings for the channel that the video is displayed on).

The listings in display300are of different sizes (i.e., listing306is larger than listings308,310, and312), but if desired, all the listings may be the same size. Listings may be of different sizes or graphically accentuated to indicate degrees of interest to the user or to emphasize certain content, as desired by the content provider or based on user preferences. Various systems and methods for graphically accentuating content listings are discussed in, for example, Yates, U.S. Patent Application Publication No. 2010/0153885, filed Nov. 12, 2009, which is hereby incorporated by reference herein in its entirety.

Users may access content and the media guidance application (and its display screens described above and below) from one or more of their user equipment devices.FIG.4shows a generalized embodiment of illustrative user equipment device400. More specific implementations of user equipment devices are discussed below in connection withFIG.5. User equipment device400may receive content and data via input/output (hereinafter “I/O”) path402. I/O path402may provide content (e.g., broadcast programming, on-demand programming, Internet content, content available over a local area network (LAN) or wide area network (WAN), and/or other content) and data to control circuitry404, which includes processing circuitry406and storage408. Control circuitry404may be used to send and receive commands, requests, and other suitable data using I/O path402. I/O path402may connect control circuitry404(and specifically processing circuitry406) to one or more communications paths (described below). I/O functions may be provided by one or more of these communications paths, but are shown as a single path inFIG.4to avoid overcomplicating the drawing.

A user may send instructions to control circuitry404using user input interface410. User input interface410may be any suitable user interface, such as a remote control, mouse, trackball, keypad, keyboard, touch screen, touchpad, stylus input, joystick, voice recognition interface, or other user input interfaces. Display412may be provided as a stand-alone device or integrated with other elements of user equipment device400. For example, display412may be a touchscreen or touch-sensitive display. In such circumstances, user input interface410may be integrated with or combined with display412. Display412may be one or more of a monitor, a television, a liquid crystal display (LCD) for a mobile device, amorphous silicon display, low temperature poly silicon display, electronic ink display, electrophoretic display, active matrix display, electro-wetting display, electrofluidic display, cathode ray tube display, light-emitting diode display, electroluminescent display, plasma display panel, high-performance addressing display, thin-film transistor display, organic light-emitting diode display, surface-conduction electron-emitter display (SED), laser television, carbon nanotubes, quantum dot display, interferometric modulator display, or any other suitable equipment for displaying visual images. In some embodiments, display412may be HDTV-capable. In some embodiments, display412may be a 3D display, and the interactive media guidance application and any suitable content may be displayed in 3D. A video card or graphics card may generate the output to the display412. The video card may offer various functions such as accelerated rendering of 3D scenes and 2D graphics, MPEG-2/MPEG-4 decoding, TV output, or the ability to connect multiple monitors. The video card may be any processing circuitry described above in relation to control circuitry404. The video card may be integrated with the control circuitry404. Speakers414may be provided as integrated with other elements of user equipment device400or may be stand-alone units. The audio component of videos and other content displayed on display412may be played through speakers414. In some embodiments, the audio may be distributed to a receiver (not shown), which processes and outputs the audio via speakers414.

The guidance application may be implemented using any suitable architecture. For example, it may be a stand-alone application wholly-implemented on user equipment device400. In such an approach, instructions of the application are stored locally (e.g., in storage408), and data for use by the application is downloaded on a periodic basis (e.g., from an out-of-band feed, from an Internet resource, or using another suitable approach). Control circuitry404may retrieve instructions of the application from storage408and process the instructions to generate any of the displays discussed herein. Based on the processed instructions, control circuitry404may determine what action to perform when input is received from input interface410. For example, movement of a cursor on a display up/down may be indicated by the processed instructions when input interface410indicates that an up/down button was selected.

User equipment device400ofFIG.4can be implemented in system500ofFIG.5as user television equipment502, user computer equipment504, wireless user communications device506, or any other type of user equipment suitable for accessing content, such as a non-portable gaming machine. For simplicity, these devices may be referred to herein collectively as user equipment or user equipment devices, and may be substantially similar to user equipment devices described above. User equipment devices, on which a media guidance application may be implemented, may function as a standalone device or may be part of a network of devices. Various network configurations of devices may be implemented and are discussed in more detail below.

A user equipment device utilizing at least some of the system features described above in connection withFIG.4may not be classified solely as user television equipment502, user computer equipment504, or a wireless user communications device506. For example, user television equipment502may, like some user computer equipment504, be Internet-enabled allowing for access to Internet content, while user computer equipment504may, like some television equipment502, include a tuner allowing for access to television programming. The media guidance application may have the same layout on various different types of user equipment or may be tailored to the display capabilities of the user equipment. For example, on user computer equipment504, the guidance application may be provided as a web site accessed by a web browser. In another example, the guidance application may be scaled down for wireless user communications devices506.

In system500, there is typically more than one of each type of user equipment device but only one of each is shown inFIG.5to avoid overcomplicating the drawing. In addition, each user may utilize more than one type of user equipment device and also more than one of each type of user equipment device.

The user equipment devices may be coupled to communications network514. Namely, user television equipment502, user computer equipment504, and wireless user communications device506are coupled to communications network514via communications paths508,510, and512, respectively. Communications network514may be one or more networks including the Internet, a mobile phone network, mobile voice or data network (e.g., a 4G or LTE network), cable network, public switched telephone network, or other types of communications network or combinations of communications networks. Paths508,510, and512may separately or together include one or more communications paths, such as, a satellite path, a fiber-optic path, a cable path, a path that supports Internet communications (e.g., IPTV), free-space connections (e.g., for broadcast or other wireless signals), or any other suitable wired or wireless communications path or combination of such paths. Path512is drawn with dotted lines to indicate that in the exemplary embodiment shown inFIG.5it is a wireless path and paths508and510are drawn as solid lines to indicate they are wired paths (although these paths may be wireless paths, if desired). Communications with the user equipment devices may be provided by one or more of these communications paths, but are shown as a single path inFIG.5to avoid overcomplicating the drawing.

System500includes content source516and media guidance data source518coupled to communications network514via communication paths520and522, respectively. Paths520and522may include any of the communication paths described above in connection with paths508,510, and512. Communications with the content source516and media guidance data source518may be exchanged over one or more communications paths, but are shown as a single path inFIG.5to avoid overcomplicating the drawing. In addition, there may be more than one of each of content source516and media guidance data source518, but only one of each is shown inFIG.5to avoid overcomplicating the drawing. (The different types of each of these sources are discussed below.) If desired, content source516and media guidance data source518may be integrated as one source device. Although communications between sources516and518with user equipment devices502,504, and506are shown as through communications network514, in some embodiments, sources516and518may communicate directly with user equipment devices502,504, and506via communication paths (not shown) such as those described above in connection with paths508,510, and512.

In a third approach, users of user equipment devices inside and outside a home can use their media guidance application to communicate directly with content source516to access content. Specifically, within a home, users of user television equipment502and user computer equipment504may access the media guidance application to navigate among and locate desirable content. Users may also access the media guidance application outside of the home using wireless user communications devices506to navigate among and locate desirable content.

In a fourth approach, user equipment devices may operate in a cloud computing environment to access cloud services. In a cloud computing environment, various types of computing services for content sharing, storage or distribution (e.g., video sharing sites or social networking sites) are provided by a collection of network-accessible computing and storage resources, referred to as “the cloud.” For example, the cloud can include a collection of server computing devices, which may be located centrally or at distributed locations, that provide cloud-based services to various types of users and devices connected via a network such as the Internet via communications network514. These cloud resources may include one or more content sources516and one or more media guidance data sources518. In addition or in the alternative, the remote computing sites may include other user equipment devices, such as user television equipment502, user computer equipment504, and wireless user communications device506. For example, the other user equipment devices may provide access to a stored copy of a video or a streamed video. In such embodiments, user equipment devices may operate in a peer-to-peer manner without communicating with a central server.

FIG.6is a flowchart of an illustrative process for educating a user about terminology associated with a sporting event, in accordance with some embodiments of the disclosure. It should be noted that process600or any step thereof could be performed on, or provided by, any of the devices shown inFIGS.4-5. For example, process600may be executed by control circuitry404(FIG.4) as instructed by a media guidance application implemented on a user device (e.g., user equipment devices502,504, and/or506(FIG.5)) in order to educate a user about terminology associated with a sporting event. In addition, one or more steps of process600may be incorporated into or combined with one or more steps of any other process or embodiment (e.g., as described in relation toFIGS.1and7-11).

At step602, control circuitry404(FIG.4) detects that a user is currently accessing content corresponding to a sporting event of a given type. Referring back to the overarching example in which the user is viewing a baseball game featuring the New York Yankees and the Boston Red Sox, control circuitry404may extract metadata from the media guidance data source518(FIG.5) associated with the baseball game, such as the name and the description of the content, to search for references to a sport. Control circuitry404may specifically determine that the name of a sport (e.g., baseball) is found in the name or description of the content. Accordingly, control circuitry404may determine that the content is associated with the identified sporting event.

At step604, control circuitry404(FIG.4) determines a frequency representing how often the user views sporting events of the given type to establish an education level of the user associated with the given type of sporting event. For example, control circuitry404may refer to the viewing history of the user in storage408(FIG.4) to identify media assets the user has previously viewed that correspond to the sporting event type. Suppose that control circuitry404identifies several media assets that the user previously accessed that correspond to baseball. Control circuitry404may determine the time of access for each media asset and determine a frequency value (e.g., accessed one per week, twice a month, etc.) based on the number of times the user accessed the media assets in a given period of time. Based on the frequency value, control circuitry404may use a lookup table in storage408to determine an education level of the user in terms of the sport. For example, control circuitry404may determine that the frequency of one time per day (e.g., the user views content associated with baseball on daily basis) indicates that the user has an “advanced” understanding of baseball. Therefore, the education level of the user may be “advanced” for baseball-related content.

At step606, control circuitry404(FIG.4) detects a term unique to the given type of sporting event in the content. Control circuitry404may actively monitor for terms by analyzing any closed-captioning data associated with the content, sports commentary audio, or visual cues such as an in-game overlay of metrics when a player comes to bat. The media guidance data source518(FIG.5) may provide this information. Control circuitry404may utilize computer vision to process visual information, and natural language processing to identify words. For example, the user may be viewing a baseball game and the sports commentator may use the term “slugging percentage.” Control circuitry404may first identify the term “slugging percentage” using the processes mentioned, and then use a lookup table to determine that the term is unique to the sporting event type, baseball.

At step608, in response to determining that the education level of the user is less than a threshold, control circuitry404(FIG.4) presents an explanation of the term on display412(FIG.4) to the user while the user accesses the content. The threshold may be a value associated with the identified term. For example, the lookup table in storage408(FIG.4) that indicates whether the term is unique to the sporting event type may also provide a definition of the term and a threshold that represents the maximum education level that requires an explanation of the term. Suppose that the user's education level is “advanced” and the threshold is “expert,” a value greater than the user's education level. In response to determining that the user's education level is lower than the threshold, control circuitry404may determine that the term “slugging percentage” should be provided and may generate, for display, an explanation to the user as he/she views the content.

FIG.7is a flowchart of a detailed illustrative process for educating a user about terminology associated with a sporting event, in accordance with some embodiments of the disclosure. It should be noted that process700or any step thereof could be performed on, or provided by, any of the devices shown inFIGS.4-5. For example, process700may be executed by control circuitry404(FIG.4) as instructed by a media guidance application implemented on a user device (e.g., user equipment devices502,504, and/or506(FIG.5)) in order to educate a user about terminology associated with a sporting event. In addition, one or more steps of process700may be incorporated into or combined with one or more steps of any other process or embodiment (e.g., as described in relation toFIGS.1,6and8-11).

At step702, control circuitry404(FIG.4) detects that a user is currently accessing content corresponding to a sporting event of a given type. The content may include at least one of a linear media asset (e.g., television broadcast of a sports event), an on-demand media asset (e.g., a recording of a sports documentary), and social chatter on a social platform associated with the user (e.g., sports forum or discussion). Control circuitry404may access the content from the media content source516(FIG.5) on the user's device, such as user television equipment502, user computer equipment504, or a wireless communications device506(FIG.5). Suppose that the user is accessing a sports documentary about Babe Ruth, an iconic baseball player. Control circuitry404may retrieve metadata from the media guidance data source518(FIG.5) associated with the documentary to determine what the user is viewing. The metadata, as generated by the content provider, may include information such as the content's name, description, transmission time, year of production, etc. In this case, control circuitry404may determine that the name of the content the user is currently watching is “Babe Ruth: A Look into the Life of Baseball's Finest,” which has a description listed as “a through biography of the New York Yankees legend, focusing on the iconic baseball player's career.” Control circuitry404may retrieve a sports database from storage408(FIG.4) that lists a variety of sports (e.g., baseball, basketball, tennis, etc.). Control circuitry404may then search the name of the content, and/or the description, for a sport listed in the sports database. For example, control circuitry404may retrieve the term “baseball” from the sports database, search for “baseball” in the strings of the name and/or description, and determine that “baseball” is found in the string(s) (e.g., in the name of the content or in the description). Thus, control circuitry404detects that the user is currently accessing content corresponding to the sporting event type, baseball.

At step704, control circuitry404(FIG.4) searches, based on the given type of the sporting event type, a viewing history associated with the user, to identify a plurality of media assets corresponding to sporting events of the given type. For example, control circuitry404may retrieve a user profile associated with the user from storage408(FIG.4) that provides information such as the user's viewing history, content preferences, bookmarks, etc. Control circuitry404may access the viewing history of the user to determine the media assets the user has viewed that correspond to the sport event detected. For example, control circuitry404may search for the term “baseball” in the metadata of the media assets (e.g., name, description) found in the viewing history. Suppose that the user has rarely watched baseball. Control circuitry404may determine that the viewing history only has three instances of media assets corresponding to baseball.

At step706, control circuitry404(FIG.4) retrieves a viewing time associated with each of the plurality of media assets. For example, the viewing history in storage408(FIG.4) may also list time stamps of the times the user viewed the media assets. Consider the three media assets corresponding to baseball: game 1, game 2, and the documentary currently being accessed. Control circuitry404may determine the viewing times, based on the metadata of the media assets, as Oct. 2, 2015 at 5:00 pm, Oct. 2, 2016 at 6:00 pm, and Oct. 2, 2017 at 5:30 pm, respectively.

At step708, control circuitry404(FIG.4) compares an average of differences between the viewing times associated with each of the plurality of media assets. For example, control circuitry404may first determine the difference between the three media assets mentioned previously. The difference between the viewing time of game 1 and game 2 is one year and the difference between game 2 and the documentary is one year. Therefore, control circuitry404may determine that the average of differences between media assets is one year.

At step710, control circuitry404(FIG.4) determines, based on the computed average, a frequency representing how often the user views sporting events of the given type. The frequency may be a quantitative (e.g., 5 times per week, 10 times per month, etc.) or a qualitative value (e.g., often, very often, rarely, etc.). For example, control circuitry404may determine that the average difference between the media asset viewing times is one year. Therefore, the user watches media assets corresponding to baseball once a year. If control circuitry404relies on a qualitative frequency, control circuitry404may determine classifications of various numerical values. For example, the frequency 1 times per week may be classified as “not often,” 3 times per week may be classified as “average,” 5 times per week may be classified as “often,” etc. In this case, control circuitry404may determine the frequency to be 1/52 times per week, which control circuitry404may classify as “rarely.” The user may select whether control circuitry404should use qualitative values or quantitative values through I/O Path402(FIG.4). Control circuitry404may store the user's selection in the user profile in storage408(FIG.4).

At step712, control circuitry404(FIG.4) searches a database of education levels to identify a first education level associated with the determined frequency to establish a first sport education level of the user associated with the given type of sporting event. The first sport education level may represent the level of knowledge a user has about a specific sport, and is used to determine whether certain terms should be explained to the user and how complicated the explanations can be. The database of education levels may be a lookup table (e.g., array of strings) in storage408(FIG.4) that lists education levels (e.g., some high school, high school diploma, some college, associate degree, bachelor degree, etc.) in separate rows and the frequency (e.g., rarely, average, often, etc.) in separate columns. The intersection of an education level and the frequency may indicate the first sport education level (e.g., completely new, beginner, intermediate, advanced, expert, etc.). For example, the intersection of “bachelor degree” and “often” may indicate that the user has an “advanced” first sport education level. Control circuitry404may determine the first education level of the user by requesting user input of the education level, or referring to social media (e.g., education field of user's Facebook profile) over the Internet. Suppose that the user profile in storage408indicates that the user's first education level is “high school diploma.” The frequency, as determined by control circuitry404, is “rarely.” Control circuitry404may use these inputs to look up the user's first sport education level. Based on the database of education levels, control circuitry404may determine that the user has a “beginner” first sport education level.

At step714, control circuitry404(FIG.4) processes metadata associated with the currently accessed content to identify a plurality of terms describing the sporting event type. Control circuitry404may actively monitor for terms by analyzing any closed-captioning data associated with the content, sports commentary audio, or visual cues such as an in-game overlay of metrics when a player comes to bat. The media guidance data source518(FIG.5) may provide this information. Control circuitry404may utilize computer vision to process visual information, and natural language processing to identify words. For example, in the documentary being watched by the user, the narrator may say “Babe Ruth is synonymous with homeruns.” Control circuitry404(FIG.4) may either retrieve these words from the subtitles of the documentary, or utilize speech recognition to transcribe the quote. This process is discussed in greater detail in the description ofFIG.9.

At step716, control circuitry404(FIG.4) compares the identified plurality of terms with a list of terms associated with the given type of sporting event to detect a term of the plurality of terms that is unique to the given type of sporting event in the content. For example, the closed-captioning or the commentary may include a quote “Babe Ruth is synonymous with homeruns.” Upon converting the speech to text, control circuitry404(FIG.4) may identify each word/phrase in the quote and determine the words/phrases that correspond solely to “baseball.” Control circuitry404may refer to the sports database in storage408(FIG.4) to determine a list of terms that correspond to a sporting event. These words may include technical terms, player names, team names, events, etc. In this example, control circuitry404may determine that the sports database for “baseball” includes the list of terms “Babe Ruth,” and “homeruns,” which are also found in the quote. Therefore, the words “Babe Ruth” and “homeruns” from the quote correspond to the sporting event type, baseball. Furthermore, control circuitry404may determine that the terms “Babe Ruth” and “homerun” are exclusive to “baseball” since they are not found in other sections of the sports database. In some embodiments, the sports database may feature an additional column that indicates whether a term is unique to the sport or the term's definition is unique to the sport (e.g., to account for sports that use similar terms with different definitions).

At step718, control circuitry404(FIG.4) compares the first sport education level of the user to a threshold sport education level. The threshold sport education level may be retrieved from storage408(FIG.4) and is associated with the term that is unique to the sporting event type. For example, the sports database may include a column that assigns each term a threshold sporting event educational level. In terms of baseball, terms such as “Babe Ruth,” and “homerun,” may be assigned a threshold sport education level of “beginner,” whereas “slugging percentage” may be assigned “advanced.” In this example, control circuitry404may determine that the first sport education level of the user is equal to the threshold sport education level. It should be noted that the threshold sport education level may also be a quantitative value. For example, the education levels may be ranked in a 1-10 scale where 1 represents a minimum education level and 10 represents the highest education level. Similarly, the threshold level may also be ranked in a scale from 1-10. Suppose that the sporting event type education of the user is 3 and the threshold sport education level for the terms “Babe Ruth” and “homerun” is 4, control circuitry404may determine that the user's first sport education level is less than the threshold sport education level.

At step720, control circuitry404(FIG.4) determines whether the first sport education level of the user is less than or equal to the threshold sport education level. In the case where the first sport education level is greater than the threshold sport education level, the process returns to step714and control circuitry404continues to process metadata (e.g., subtitles, visuals, audio, etc.) for new terms that are unique to the sporting event type. In response to determining that the first sport education level of the user is less than or equal to the threshold sport education level, the process advances to step722.

At step722, control circuitry404(FIG.4) presents an explanation of the term to the user while the user accesses the content. For example, control circuitry404may determine that the terms “Babe Ruth” and “homerun” have a threshold sport education level of “beginner,” which matches the user's first sport education level. Likewise, if control circuitry404is using quantitative representations of the education and threshold levels, control circuitry404may determine that the user's first sport education level is less than the threshold sport education level. In response, control circuitry404may retrieve a definition of the terms “Babe Ruth” and “homerun” from the sports database, or from the Internet. control circuitry404may then present an explanation of the terms on display412. In some embodiments, presenting the explanation of the term comprises at least one of replacing a display of the term with the explanation, presenting an overlay over the content with the explanation adjacent to the term, highlighting the term in a display, or sending the explanation to a second screen device. For example, control circuitry404may highlight the term “Babe Ruth” and “homerun” in the closed-captioning (e.g., depicted similarly in closed captioning overlay102inFIG.1) and generate an overlay that defines the term (e.g., depicted similarly in definitions overlay106inFIG.1). Alternatively, the user may replace the terms “Babe Ruth” and “homerun” in the closed-captioning with their respective definitions/explanations. If the user is listening to an audio version of the sporting event type (e.g., on the radio), control circuitry404may also dictate the explanation of the term to the user through I/O Path402(FIG.4). In some embodiments, control circuitry404may use speech recognition to wait for a portion of the audio when no sports commentary is taking place to dictate the explanation of the term. Control circuitry404may also communicate with another device on the user's network over communications network514(FIG.5). Upon identifying a second device (e.g., user television equipment502, user computer equipment504, or wireless user communications device506), control circuitry404may send the explanation to the second device in order to generate, for display, the explanation for the user.

FIG.8is a flowchart of a detailed illustrative process for presenting a second explanation of a term to the user that is more advanced than the first explanation, in accordance with some embodiments of the disclosure. It should be noted that process800or any step thereof could be performed on, or provided by, any of the devices shown inFIGS.4-5. For example, process800may be executed by control circuitry404(FIG.4) as instructed by a media guidance application implemented on a user device (e.g., user equipment devices502,504, and/or506(FIG.5)) in order to present a second explanation of a term to the user that is more advanced than the first explanation. In addition, one or more steps of process800may be incorporated into or combined with one or more steps of any other process or embodiment (e.g., as described in relation toFIGS.1,6-7and9-11).

At step802, control circuitry404(FIG.4) receives user input setting a value for the education level of the user as the first education level. For example, control circuitry404may generate an overlay on display412(FIG.4) with options for education levels (e.g., some high school, high school diploma, associate degree, etc.). The user may indicate over I/O Path402, that he/she has an education level “high school diploma.” This indicates that the user has completed high school. Accordingly, when generating explanations, control circuitry404may use vocabulary that a high school graduate can comprehend. If the user indicated an education level “masters degree,” control circuitry404would provide more advanced explanations to sports terminology. Control circuitry404may store the value set by the user in the user profile in storage408.

At step804, control circuitry404(FIG.4) detects that the user is accessing a second content corresponding to the sporting event type of the given type after a period of time of accessing the first content. For example, the user may access an on-demand media asset such as a second sports documentary about the New York Yankees, a MLB baseball team. Control circuitry404may retrieve metadata associated with the second content from the content provider and determine whether the name or description correspond to a sport in the sports database. In this case, control circuitry404may determine that the second content has metadata that references the terms “baseball” and “New York Yankees,” which are terms found in the “baseball” section of the sports database. Therefore, control circuitry404may determine that the second content corresponds to the sporting event type, baseball. Furthermore, control circuitry404may retrieve the viewing history of the user from his/her user profile in storage408(FIG.4) to determine the viewing time of the first content. Suppose that the user accessed the first content on Oct. 2, 2017. The user may be accessing the second content on Nov. 2, 2017. Thus, the period of time between the viewing time of the first content and the viewing time of the second content is one month.

At step806, control circuitry404(FIG.4) determines an increase in the frequency representing how often the user views sporting events of the given type. For example, control circuitry404may determine, based on the viewing times of the first content and the second content, that the viewing time difference is one month. In comparison, the average difference previously computed by control circuitry404was one year. Therefore, control circuitry404may detect an increase in the frequency (e.g., the user is accessing content related to the sporting event type more frequently). Alternatively, the media guidance application may re-compute the average difference between viewing times. In this case, the user has viewed, based on the viewing history, game 1, game 2, the documentary (the first content), and the second documentary (the second content). The re-computed average may indicate that the user views a media asset associated with the sporting event type every 0.7 years. Since previously the computed average indicated that the user views a media asset associated with the sport event every 1 year, control circuitry404may determine that the frequency has increased.

At step808, control circuitry404(FIG.4) searches the database of education levels to identify a second sport education level associated with the increased frequency. Suppose that qualitatively, the frequency increased from “rarely” to “occasionally.” As discussed previously, the user's education level may be “high school diploma.” As a result, control circuitry404may search the database of education levels for the sports education level that intersects at the lookup table between “high school diploma” and the frequency “occasionally.” Suppose that the intersection is the “intermediate” sports education level. Control circuitry404may identify “intermediate” as the second education level. If control circuitry404is using a quantitative scale for education levels and frequency (e.g., a scale of 1-10), control circuitry404may convert “high school diploma” to a numerical value of 3. Likewise, the numerical counterpart of “occasionally” may be 5. Based on the lookup table, these values may intersect at a second sport education level of 5. In some embodiments, control circuitry404may use the numerical values as inputs in an algorithm which outputs an appropriate sport education level.

At step810, control circuitry404(FIG.4) processes metadata associated with the second content to identify the term detected in the first content. As mentioned previously, control circuitry404may process metadata by extracting subtitles or closed-captioning data to identify words that correspond to the sporting event type. Control circuitry404may also utilize computer vision to identify metrics, terms and objects displayed in the content. This is discussed in greater detail in the description ofFIG.9. Suppose that control circuitry404identifies the term “homerun” once again.

At step812, control circuitry404(FIG.4) compares the second sport education level of the user to the threshold sport education level. Suppose that the user's second sport education level is “intermediate,” as determined by control circuitry404. The threshold sport education level of the term “homerun” may be “beginner,” as indicated in the sports database in storage408(FIG.4). Similarly, the quantitative counterpart of the threshold sport education level may be 4, and the user's second sport education level may be 5.

At step814, control circuitry404(FIG.4) determines whether the second sport education level of the user is greater than the threshold sport education level. As indicated in the previous step, the threshold sport education level “beginner” is less than the second sport education level “intermediate.” If control circuitry404determined otherwise, the process would return to step810and control circuitry404would continue to monitor audio, visuals, and metadata, for terms that are unique to the sport.

At step816, in response to determining that the second sport education level of the user is greater than the threshold sport education level, control circuitry404(FIG.4) determines whether the second sport education level of the user is less than a maximum threshold sport education level. In this case, the maximum threshold sport education level may be 10 (e.g., quantitatively) or “expert” (e.g., qualitatively) and is therefore greater than the user's second sport education level. The maximum threshold may represent the highest value of knowledge that can be achieved by a user in terms of the sporting event type. A user that has an “expert” sport education level may not need definitions of basic terms such as “Babe Ruth” or “homerun.”

At step818, in response to determining that the second sport education level of the user is greater than the threshold sport education level but less than a maximum threshold sport education level, control circuitry404(FIG.4) presents a second explanation of the term to the user that is more advanced than the first explanation. The sports database in storage408(FIG.4) may include multiple definitions/explanations for terms based on the sport education level of a user. For example, the definition for “Babe Ruth” presented to a user with a “beginner” sport education level may simply be “a famous baseball player most well-known for his time with the New York Yankees.” Alternatively, the sports database may provide the definition for “Babe Ruth” presented to a user with an “advanced” sport education level as “an iconic baseball player, recognized in the MLB Hall of Fame, who is known for excellent pitching and hitting—an uncommon duo.”

At step820, control circuitry404(FIG.4) presents the user with an option to explain the terms/metrics for other users in response to determining that the user's second sport education level is not less than the maximum threshold sport education level. In this case, control circuitry404may classify the user as an expert in the sport. Accordingly, control circuitry404may generate an option on display412(FIG.4) allowing the user to choose whether he/she wants to provide an explanation of the term/metric for other users that may access the content. If the user accepts to provide an explanation, control circuitry404may generate a user input interface410(FIG.4) that allows the user to enter an explanation. Control circuitry404then collects the user's explanation and may advance to step1006inFIG.10.

FIG.9is a flowchart of a detailed illustrative process for processing metadata to identify a plurality of terms describe the sporting event type, in accordance with some embodiments of the disclosure. It should be noted that process900or any step thereof could be performed on, or provided by, any of the devices shown inFIGS.4-5. For example, process900may be executed by control circuitry404(FIG.4) as instructed by a media guidance application implemented on a user device (e.g., user equipment devices502,504, and/or506(FIG.5)) in order to process metadata to identify a plurality of terms describe the sporting event type. In addition, one or more steps of process900may be incorporated into or combined with one or more steps of any other process or embodiment (e.g., as described in relation toFIGS.1,6-8and10-11).

At step902, control circuitry404(FIG.4) begins the process of identifying a plurality of terms that describe the sporting event type. For example, if the user is viewing a live baseball game, control circuitry404may determine whether closed-captioning is available and may also retrieve information about the layout the content provider uses for placing metrics and overlays on the screen. Control circuitry404may thus identify the plurality of terms in real-time. If the user is simply accessing on-demand content that was previously recorded, control circuitry404may scan the entire content to identify terms before the user even reaches the term during playback.

At step904, control circuitry404(FIG.4) receives closed-captioning information corresponding to the currently accessed content. For example, control circuitry404(FIG.4) may determine that closed-captioning is available in the currently accessed content. Control circuitry404(FIG.4) may extract the closed-captioning data and identify words associated with the sporting event type. For example, closed-captioning may provide quotes to control circuitry404such as “Babe Ruth's base-hit was during the World Series was crucial.” Control circuitry404may parse the quote into separate words/phrases and cross reference them with the sports database in storage408(FIG.4) (e.g., performed inFIG.7, step716).

At step906, control circuitry404(FIG.4) converts speech (e.g., sports commentary) in the currently accessed content to text using natural language processing (e.g., speech recognition). For example, the content may not have closed-captioning information associated with it. As a result, when the narrator says “Babe Ruth's base-hit was during the World Series was crucial,” control circuitry404may transcribe the quote, separate the words/phrases and cross reference them with the sports database in storage408(FIG.4) (e.g., performed inFIG.7, step716).

At step908, control circuitry404(FIG.4) processes visual information presented in the content to detect metrics of the sporting event type. For example, control circuitry404may utilize computer vision processes (e.g., segmentation, edge detection, classification) and natural language processing to identify visual information in the content. It should be noted that content providers (e.g., FOX, ESPN) often place metrics in the same part of the screen for each game of a sport. For example, FOX may place a scoreboard on the top left part of the screen for every MLB baseball game. The content of the scoreboard may also be placed in the same positions (e.g., team name, followed by points of the team, followed by the inning number, etc.). When utilizing computer vision to classify numbers and words, control circuitry404may refer to a presentation database in storage408(FIG.4) that includes pixel coordinates outlining the positions of various metrics and overlays generated by a content provider for a sporting event. Control circuitry404may then limit its processing to those coordinates to identify metrics with more efficiency. Using this approach for example, control circuitry404may process visuals such as the term “Homerun” appearing on the display and overlays including Babe Ruth's batting percentages. If information is not available in the presentations database for a particular content provider, control circuitry404may consider the entire display while running computer vision processes.

At step910, control circuitry404(FIG.4) identifies words in the closed-captioning information, text, and the metrics as the metadata. For example, control circuitry404may gather all of the words/metrics identified through the various processes described previously (e.g., computer vision, speech recognition, etc.) and identify them as the metadata. If the content was previously recorded, control circuitry404may scan the entire content for terms and also list the points at which the word/metric was mentioned (e.g., “homerun” mentioned 1 minute 23 second into the content). Control circuitry404may store this information alongside the metadata of the content in storage408(FIG.4).

FIG.10is a flowchart of a detailed illustrative process for generating the explanation of the term based on set of inputs from a social network, in accordance with some embodiments of the disclosure. It should be noted that process1000or any step thereof could be performed on, or provided by, any of the devices shown inFIGS.4-5. For example, process1000may be executed by control circuitry404(FIG.4) as instructed by a media guidance application implemented on a user device (e.g., user equipment devices502,504, and/or506(FIG.5)) in order to generate the explanation of the term based on set of inputs from a social network. In addition, one or more steps of process1000may be incorporated into or combined with one or more steps of any other process or embodiment (e.g., as described in relation toFIGS.1,6-9and11).

At step1002, control circuitry404(FIG.4) transmits the term to a social network associated with the user. The social network may be any platform that allows users to communicate with each other by posting comments, images, videos, etc. (e.g., Facebook, Twitter, Reddit, etc.) on the Internet. Control circuitry404may post the term detected “foul-ball” to a social network that the user is associated with, while requesting an explanation for the term. For example, control circuitry404may refer to the user profile to determine the social media accounts the user has.

At step1004, control circuitry404(FIG.4) receives input from a plurality of users on the social network through I/O Path402(FIG.4), each input providing a given explanation of the term. For example, three users may provide an explanation of “foul-ball.” User 1 may post “a ball that lands past a boundary of the ballpark.” User 2 may post “a ball that lands beyond the marked lines of the play field.” User 3 may post “a ball that is not in the boundary of the playing field.”

At step1006, control circuitry404(FIG.4) identifies a set of the inputs from the plurality of users having explanations in common. For example, control circuitry404may identify words and their synonyms to determine similarities between the explanations posted. In this case, control circuitry may identify a majority of the users start their explanations with “a ball that lands” and end with “the playing field.” Furthermore, control circuitry404may recognize “past” and “beyond” as synonyms based on dictionaries available from the Internet.

At step1008, control circuitry404(FIG.4) determines whether input from the user that identifies a set of experts on the social network for the given type of sporting event has been received. For example, control circuitry404may identify other users that also use the media guidance application and have a sport education level equal to the maximum threshold sport education level. Alternatively, control circuitry404may identify individuals or companies (e.g., MLB, NBA, NHL, etc.) that are a part of the social network, and are associated with the sporting event type. For example, these individuals may be sports announcers, players, coaches, trainers, analysts, etc. Due to their direct association with the sport, the media guidance application may identify the individuals and companies as a set of experts. Control circuitry404may prompt the user whether he/she wishes to confirm the experts identified by control circuitry404. If the user chooses not to confirm the experts, the process may advance to step1114. In contrast, if the user confirms the experts using I/O Path402(FIG.4), control circuitry404may list the identified experts in an expert database in storage408(FIG.4). Whenever a user posts an explanation of a term on the social network, control circuitry404may cross reference the name/username of the user with the expert database to determine whether the user is an expert of the sport. Each sport may have its own section in the expert database with different experts.

At step1010, control circuitry404(FIG.4) limits transmission of the term to the identified set of experts. For example, control circuitry404may only consider the explanations from the experts when generating an explanation for the user based on the set of inputs that are common among each explanation posted on the social network. In some cases, control circuitry404may generate a social network profile, post a query for defining the term, and only allow experts to post on the profile with potential explanations.

At step1112, control circuitry404(FIG.4) generates the explanation of the term based on the set of inputs from the experts. At step1114, control circuitry404generates the explanation of the term based on the set of the inputs of all users that answered. In each case, the generation process is the same. For example, based on the similarities of the posted explanations, control circuitry404may construct an explanation, which combines a set of inputs that are common, such as “a ball that lands beyond a boundary of the playing field.” In some embodiments, control circuitry404may directly select the explanation with a number of acknowledgments (e.g., likes, retweets, comments, etc.) greater than an acknowledgment threshold, as the explanation that will be displayed to users that come across the term while accessing content. For example, if user 2 received the 100 likes for an explanation that he/she gave, control circuitry404may refer to the user profile in storage408(FIG.4) to retrieve the acknowledgment threshold (e.g., 50). In response to determining that the amount of acknowledgments the user's explanation received is greater than the acknowledgment threshold, control circuitry404may select the explanation, instead of generating a new one based on the set of inputs.

FIG.11is a flowchart of a detailed illustrative process for modifying a metric that is displayed based on the first sport education level of the user, in accordance with some embodiments of the disclosure. It should be noted that process1100or any step thereof could be performed on, or provided by, any of the devices shown inFIGS.4-5. For example, process1100may be executed by control circuitry404(FIG.4) as instructed by a media guidance application implemented on a user device (e.g., user equipment devices502,504, and/or506(FIG.5)) in order to modify a metric that is displayed based on the first sport education level of the user. In addition, one or more steps of process1100may be incorporated into or combined with one or more steps of any other process or embodiment (e.g., as described in relation toFIGS.1and6-10).

At step1102, control circuitry404(FIG.4) detects display of a metric of the sporting event type in the currently accessed content. For example, during a baseball game, a player may be approaching home plate to bat. As a result, the player's batting statistics may appear on the display of the user. Control circuitry404may identify the metrics by using computer vision (e.g., segmentation, edge detection, classification). This is further discussed in the description ofFIG.9.

At step1104, in response to identifying a display of a metric (e.g., a plurality of statistics), control circuitry404(FIG.4) begins the process of modifying the metric that is displayed, based on the sport education level of the user.

At step1106, control circuitry404(FIG.4) ranks the plurality of statistics based on an importance level associated with each statistic. Revisiting the previous example, when a player's batting statistics are shown on the screen, the metrics may include “batting average,” “on-base percentage,” “slugging percentage,” and “on-base plus slugging percentage.” Control circuitry404may determine the importance of each statistic by referring to the sports database in storage408(FIG.4). The sports database may include a section that lists metrics associated with a sport, and organizes them based on importance. Furthermore, each metric may have a threshold sport education level associated with it. The importance of a metric may be a pre-determined value (e.g., on a scale from 1-10 or a qualitative description such as “very important”) assigned by the sports organization associated with the sporting event type (e.g., MLB is associated with baseball). Suppose that accordingly, control circuitry404ranks “batting average” as 1 (e.g., first-most important), “on-base percentage” as 2, “slugging percentage” as 3, and “on-base plus slugging percentage” as 4 (e.g., least-most important), based on the importance listed in the sports database.

In some embodiments, control circuitry404may determine the importance of a metric based on the frequency at which appears during a sporting event. For example, control circuitry404may analyze previous media assets associated with the sporting event type and count the number of references made to a specific metric. Control circuitry404may then organize the list of metrics in the sports database based on the frequency of appearance of a metric.

At step1108, control circuitry404(FIG.4) determines whether the first sport education level of the user is greater than the threshold sport education level. Control circuitry404may retrieve the first sport education level from the user profile in storage408(FIG.4) and the threshold sport education level from the metrics section of the sports database in storage408. Suppose that control circuitry404determines that the first sport education level, on a scale of 1-10, is 5 and the threshold sport education level is 3. Therefore, control circuitry404may determine that the user's first sport education level is greater than the threshold sport education level.

At step1110, control circuitry404(FIG.4) determines whether the first sport education level of the user is less than a maximum threshold sport education level. As mentioned previously, the maximum threshold sport education level represents the highest sport education a user can achieve and signifies that the user has expert knowledge of the sport. If the scale of education levels is 1-10, the maximum threshold sport education level is 10. Therefore, control circuitry404may determine that the user's first sport education level is less than the maximum threshold sport education level.

At step1112, control circuitry404(FIG.4) removes a first subset of the plurality of statistics being displayed that is associated with a rank greater than a first threshold rank, in response to determining that the first sport education level of the user is greater than the threshold sport education level and less than a maximum threshold sport education level. Suppose that the first threshold rank is 2 (e.g., retrieved from the sports database in storage408(FIG.4)), the user's first education level is 5, the threshold sport education level is 3, and the maximum threshold sport education level is 10. Control circuitry404may determine that the user's first sport education level is greater than the threshold sport education level and is lower than the maximum threshold sport education level. This may signify that the user is familiar enough with the sport to understand a certain set of terms or metrics, but not perhaps the complex ones. It should be noted that the terms and metrics that appear more frequently may be marked with greater importance. Accordingly, control circuitry404may remove a first subset of the plurality of statistics that is associated with a rank lower than the first threshold rank. In this example, control circuitry404may remove “slugging percentage” and “on-base plus slugging percentage” from display412(FIG.4) because they rank lower than the first threshold rank.

Suppose that at step1108, control circuitry404(FIG.4) determines that the first sport education level of the user is less than the threshold sport education level. In response, the process may advance to step1114where control circuitry404removes a second subset of the plurality of statistics being displayed that is associated with a rank lower than a second threshold rank, wherein the second threshold rank is greater than the first threshold rank, and wherein the second subset includes the first subset. For example, the user's sport education level may be 2 and the threshold sport education level may be 3. Therefore, control circuitry404may determine that the user's sport education level is lower than the threshold sport education level (e.g., the user is not fully familiar with the sport). The second threshold rank may be 1, a value greater than the first threshold rank. Control circuitry404may therefore remove all metrics that rank below the second threshold rank. In this case, the second subset would therefore include “on-base percentage,” “slugging percentage,” and “on-base plus slugging percentage.” It should be noted that “slugging percentage” and “on-base plus slugging percentage” were part of the first subset. Thus, the second subset includes the first subset. In some embodiments, in place of the removed metrics, control circuitry404may present trivia and fun facts to the user on display412(FIG.4) about the metrics that are still being displayed to the user. For example, control circuitry404may replace the section displaying “on-base percentage,” “slugging percentage,” and “on-base plus slugging percentage” with an overlay with trivia about “batting average” (e.g., “Did you know: Player X currently has the highest batting average in the league”).

At step1116, control circuitry404(FIG.4) presents the user with an option to explain the metrics for other users in response to determining that the user's first sport education level is not less than the maximum threshold sport education level. In this case, control circuitry404may classify the user as an expert in the sport. Accordingly, control circuitry404may generate an option on display412(FIG.4) allowing the user to choose whether he/she wants to provide an explanation of the term/metric for other users that may access the content. If the user accepts to provide an explanation, control circuitry404may generate a user input interface410(FIG.4) that allows the user to enter an explanation. Control circuitry404then collects the user's explanation and may advance to step1006inFIG.10.