Systems and methods for optimizing delivery of content recommendations

The system and methods described herein provide content recommendations to user equipment timed to reduce interruption of content. A content recommendation application detects output of first content and determines viewing metrics for the first content. Using the determined viewing metrics, the content recommendation application determines whether output of a content recommendation should be blocked. In response to determining that the viewing metrics indicate output of the content recommendation should be blocked, the content recommendation application blocks the content recommendation. Upon receiving an input changing output of the first content to output of a second content, the content recommendation application unblocks and outputs the content recommendation.

BACKGROUND

The present disclosure is directed to delivering content recommendations and, more particularly, to systems and methods that time delivery of content recommendations based on a user's engagement with content.

SUMMARY

Delivering timely and unobtrusive content recommendations presents difficulties, particularly for real-time content (e.g., sports matches). Recommendations (e.g., presented as notifications or alerts) may overwhelm the user's viewing experience and distract the user from content with which the user is engaged. If a system, on the other hand, holds recommendations until a user finishes consuming content, then the recommendation may become stale.

Solutions over conventional systems for providing a user with timely content recommendations, especially recommendations for real-time content (e.g., sports games), are described herein. The systems and methods described herein achieve benefits over conventional systems by timing the display of recommendations for a time that will have less likelihood of distracting a user from the current content. A content recommendation system determines content that may be interesting to the user is available. The content recommendation system determines the user's engagement level with content currently output by the user equipment. The content recommendation system then, based on the user's engagement level, determines whether to present the content recommendation at the present time or whether to block the recommendation and hold it for later presentation. For example, if the user has been watching a show for less than a minute, the system may consider that to be a low level of engagement, whereas if the user has been watching a show for 10 minutes that may be considered a high level of engagement. Thus, the content recommendation system takes into account not only the content recommendations but also the user's engagement before delivering content recommendations. The content recommendation system may subsequently receive an indication that the user's engagement level with content has changed. For example, if the content recommendation system detects a command to change from one piece of content to a second piece of content, the content recommendation system may reinterpret the engagement level. Upon detecting such a change, the content recommendation system unblocks the content recommendation and causes the recommendation to be presented to the user.

Several techniques may be used by the systems and methods described herein to determine a user's engagement level with content being presented. As discussed above, the content recommendation system may track how long a user has been consuming the content and compare that time against one or more thresholds to determine an engagement level. For example, less than one minute may be a low level of engagement, between one and five minutes may be a medium level of engagement, and over five minutes may be a high level of engagement. In some embodiments, these thresholds may be adjusted over time and refined to account for a user's reactions to content recommendations. The content recommendation system may also consider the user's content preferences and how those preferences correlate with the content to determine engagement. For example, if the user's content preferences indicate a strong affinity for animation movies, and the current content is an animation movie, the system may determine the user has a high level of engagement with the current content. Further, the content recommendation system may employ a set of weights corresponding with different preferences and the strength of the match to determine engagement levels. In some embodiments, the content recommendation system may take into account interaction logs between a user and a plurality of devices to determine engagement. For example, a user is tuned to a channel but has several recent interactions with a mobile device may be considered to have a low level of engagement with the content (e.g., the user is interacting with a smartphone in a way that indicates a low level of engagement with the content). In another example, a content recommendation system may routinely poll user equipment to obtain an engagement level of the user with current content. A user equipment device may employ gaze detection techniques to determine a user's engagement level with content and the content recommendation system may obtain that information from the user equipment.

In some embodiments, the content recommendation system may balance the user's engagement level with the user's predicted interest in the recommendation. The content recommendation system may access the user's content preferences and correlate those preferences with information about the content to be recommended. For example, if the user is a baseball fan, then his content preferences may indicate preferred teams or may indicate he watches baseball games in the later innings. The content recommendation system may then retrieve information about a current game and determine the game matches criteria associated with the user's content preferences. Thus, the system may determine a particular game is associated with a high level of predicted interest. In that scenario, the content recommendation system may present the content recommendation even though a user's engagement level with current content is also high. In some embodiments, the predicted interest may be a calculated value (e.g., an integer value) calculated from a combination of interest weights being matched to attributes of the content being recommended. As described below, the predicted interest level may be compared against the engagement level and/or a set of interest thresholds when the content recommendation system determines how to process the content recommendation.

Several techniques may be employed to determine a predicted interest level for a piece of content being recommended. As discussed above, the content recommendation system may compare information about the content with the user's preferences to build a predicted interest level. Additionally, or alternatively, the content recommendation system may access information about the content that is untethered to the user to generate the predicted interest level. For example, the score of a game, the time remaining, the number of people currently watching a game, the ranks of the teams involved, the frequency of scoring in a game, the amount of social media posts about a game, and the number of commentators presenting discussions about a game are all potential indicators for whether a game is interesting. The content recommendation system may weigh such factors into the calculation of a predicted interest level.

Thus, the systems and methods described herein solve the problem of balancing the need to inform a user of content recommendations that may lose value after the passing of time with the user's desire to be free of distracting notification messages. The techniques described herein present content recommendations at times when a user is less likely to find them obtrusive, either because the user is less engaged with the content being interrupted or because the content recommendation rises above a threshold necessitating prompt notification.

DETAILED DESCRIPTION OF THE DRAWINGS

FIG. 1shows an illustrative series of user interface screens on a content consumption device in a content recommendation system that times delivery of content recommendations based on a user's engagement with content. Specifically,FIG. 1depicts user equipment102at three time points: A, B, and C. User equipment102is depicted as a tablet device inFIG. 1. In some embodiments, user equipment102may be a smartphone, set-top box, personal computer, or other device suitable for rendering content (e.g., movies, television shows, linear programming, and over-the-top (OTT) content). At time point A, user equipment102is displaying a first content item104A (illustrated as an animated superhero movie). At time point A, the user equipment102is also displaying a time bar106that includes a current position indicator108that is approximately 20 percent down the time bar for the first content item104A.

InFIG. 1, a content recommendation system has generated a content recommendation110for a user interacting with user equipment102. Specifically, the content recommendation system generated a recommendation for a baseball game that is in the bottom of the ninth inning and has a score of four to three. But the content recommendation system has determined to block the content recommendation, depicted with the “X”112over the content recommendation110, at time point A, in favor of later presentation of the content recommendation. For example, the content recommendation system determines a level of engagement a user has with the first content item104A being displayed by user equipment102. In the example ofFIG. 1, the content recommendation system determines that the first content item104A has been displayed to the user on user equipment102for some amount of time, perhaps 10 minutes. Based on that amount of time, the content recommendation system determines the user's engagement with the first content item104A exceeds a threshold at which the content recommendation system determines content recommendations should be blocked.

As discussed more fully below withFIGS. 5-10, the content recommendation system may employ several techniques to determine whether to present a content recommendation or block a content recommendation for later presentation. For example, blocking a content recommendation may comprise blocking transmission of a message that contains the content recommendation (e.g., a server-to-client communication). Other suitable techniques include preventing, at a user equipment, the presentation of a content recommendation prompt on a display to the user. Other suitable techniques may be employed to delay a content recommendation until such time as appropriate for user presentation.

Between time point A and time point B ofFIG. 1, the user equipment102received an indication114that the user is changing the display to a new show. In response to receiving the indication114that the user is changing the display to a new show, the content recommendation system determines that the user has a low level of engagement with the new show and that time point B would be an optimal time to present a notification to the user regarding the content recommendation.

At time point B, the user equipment102is displaying a second content item104B (illustrated as a basketball game), which a user changed to after time point A. The user equipment102is also displaying the content recommendation prompt110to the user as an invitation to change the display to the recommended content. While depicted inFIG. 1as a prompt that occurs after a user equipment102begins displaying the second content item104B, the content recommendation prompt110may be displayed by the user equipment102prior to the second content104B being displayed. For example, the user equipment102may detect a channel change command and before making the change in content, present the content recommendation prompt110.

In the example ofFIG. 1, the recommended content is a baseball game with a close score in the late stages of the game. In some embodiments, the content recommendation110provides details on the scenario of the content recommendation. In some embodiments, the content recommendation110provides options such as a “Yes” option116and a “No” option118. In the case of a user selecting the “Yes” option116, the user equipment102will change to the recommended content104C at time point C. In the case of a user selecting the “No” option118, the user equipment102will not change to the recommended content104C. For example, the user equipment102may continue to present the second content104B upon receiving a selection of the “No” option118.

In some embodiments, the user equipment102displays a notification icon120informing the user that a content recommendation is available. For example, the user equipment102may hold back the recommendation until such time as the user activates icon120.

FIG. 2is an illustrative embodiment of a display screen that may be used by a media guidance application to provide listings and other media guidance information, in accordance with some embodiments of the disclosure. Program listings display200includes a grid250arranged by time and channel that also enables access to different types of content in a single display. Grid250may include (1) a column of channel/content type identifiers202where 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 identifiers (displayed above program listings), where each time identifier (which is a cell in the row) identifies a time block of programming. Grid250also includes cells of program listings, such as program listing251(highlighted to indicate the user equipment is currently receiving the content selected at251), 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 region252. Information relating to the program listing selected by highlight region252may be provided in program information region211. Region211may 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. With a user input device, a user can also select grid forward option231or grid back option232, which shift the displayed program times for content selection. The display200may also provide several elements such as options element240, which raises a submenu to customize display200options; sort element241, which allows a user to customize the sorting of channels (e.g., sort by channel number or genre type); filter option242(e.g., allowing a user to filter listing by genre); previous-day element243(e.g., shifting the grid250by 24 hours into the past); next-day element244(e.g., shifting the grid by 24 hours into the future); and search element245(e.g., raising a search interface).

Display200may also include video region212. Video region212may 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 region212may correspond to, or be independent from, one of the listings displayed in grid250. 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 content access application display screens of the embodiments described herein.

Upon receiving a selection to change to content selected by region252, a user equipment device (such as user equipment102) may inform a content recommendation system of the change of content output such as described with reference to step506ofFIG. 5below.

Applications may be, for example, stand-alone applications implemented on user equipment devices, media content sources, or servers. For example, the media guidance application or content recommendation application may be implemented as software or a set of executable instructions, which may be stored in storage (e.g., storage308or storage414) and executed by control circuitry (e.g., control circuitry304or control circuitry410). In some embodiments, applications may be client-server applications where only a client application resides on the user equipment device (e.g., user equipment102) and a server application resides on a remote server (e.g., server404). For example, applications may be implemented partially as a client application on control circuitry304of each one of user equipment devices300and user equipment system301and partially on a remote server such as a server application (e.g., server404) running on control circuitry (e.g.,410) of the remote server. When executed by control circuitry of the remote server (such as server404), the content recommendation application may instruct the control circuitry to generate the content delivery application displays and transmit the generated displays to the user equipment devices. The content recommendation application may instruct the control circuitry of the content source to transmit data for storage on the user equipment. The client application may instruct control circuitry of the receiving user equipment to generate the content delivery application displays.

Users may access content and the applications from one or more of their media devices, i.e., user equipment.FIG. 3shows generalized embodiments of an illustrative device, i.e., user equipment102. For example, user equipment102may be a smartphone device, a tablet, or a remote control, such as illustrative user equipment300. In another example, user equipment102may be part of a user equipment system301. User equipment system301may include a set-top box316. Set-top box316may be communicatively connected to speaker314and display312. In some embodiments, display312may be a television display or a computer display. In some embodiments, set-top box316may be communicatively connected to user interface input310. In some embodiments, user interface input310may be a remote control device. Set-top box316may include one or more circuit boards. In some embodiments, the circuit boards may include control circuitry and storage (e.g., RAM, ROM, Hard Disk, Removable Disk, etc.). In some embodiments, circuit boards may include an input/output path. More specific implementations of user equipment devices are discussed below in connection withFIG. 4. Each one of user equipment devices300and user equipment system301may receive content and data via input/output (hereinafter “I/O”) path302. I/O path302may 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 circuitry304and storage308. Control circuitry304may be used to send and receive commands, requests, and other suitable data using I/O path302. I/O path302may connect control circuitry304to 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. 3to avoid overcomplicating the drawing.

Control circuitry304should be understood to mean circuitry based on one or more microprocessors, microcontrollers, digital signal processors, programmable logic devices, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), etc., and may include a multi-core processor (e.g., dual-core, quad-core, hexa-core, or any suitable number of cores) or supercomputer. In some embodiments, control circuitry may be distributed across multiple separate units, for example, multiple of the same type of processing units (e.g., two Intel Core i7 processors) or multiple different processors (e.g., an Intel Core i5 processor and an Intel Core i7 processor). In some embodiments, control circuitry304executes instructions for an application stored in memory (e.g., storage308). Specifically, control circuitry304may be instructed by the application to perform the functions discussed above and below. For example, the application may provide instructions to control circuitry304to generate the media guidance displays. In some implementations, any action performed by control circuitry304may be based on instructions received from the application.

In client server-based embodiments, control circuitry304may include communications circuitry suitable for communicating with a content recommendation application server (e.g., server404) or other networks or servers. The instructions for carrying out the above-mentioned functionality may be stored on the content recommendation application server. Communications circuitry may include a cable modem, an integrated services digital network (ISDN) modem, a digital subscriber line (DSL) modem, a telephone modem, Ethernet card, or a wireless modem for communications with other equipment, or any other suitable communications circuitry. Such communications may involve the Internet or any other suitable communications networks or paths. In addition, communications circuitry may include circuitry that enables peer-to-peer communication of user equipment devices, or communication of user equipment devices in locations remote from each other (described in more detail below).

Memory may be an electronic storage device provided as storage308that is part of control circuitry304. As referred to herein, the phrase “electronic storage device” or “storage device” should be understood to mean any device for storing electronic data, computer software, or firmware, such as random-access memory, read-only memory, hard drives, non-transitory computer readable medium, or any other suitable fixed or removable storage devices, and/or any combination of the same. Storage308may be used to store various types of content, media guidance data, and instructions for executing content access applications. Nonvolatile memory may also be used (e.g., to launch a boot-up routine and other instructions).

A user may send instructions to control circuitry304using user input interface310. User input interface310may be any suitable user interface, such as a remote control, mouse, trackball, keypad, keyboard, touchscreen, touchpad, stylus input, joystick, voice recognition interface, or other user input interfaces. Display312may be provided as a stand-alone device or integrated with other elements of each one of user equipment device300and user equipment system301. For example, display312may be a touchscreen or touch-sensitive display. In such circumstances, user input interface310may be integrated with or combined with display312. A video card or graphics card may generate the output to the display312. 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 integrated with the control circuitry304. Speakers314may be provided as integrated with other elements of each one of user equipment device300and user equipment system301or may be stand-alone units. The audio component of videos and other content displayed on display312may be played through speakers314. In some embodiments, the audio may be distributed to a receiver (not shown), which processes and outputs the audio via speakers314.

The content recommendation application and media guidance application may be implemented using any suitable architecture. For example, the media guidance application may be a stand-alone application wholly implemented on each one of user equipment device300and user equipment system301. In such an approach, instructions for the application are stored locally (e.g., in storage308), 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 circuitry304may retrieve instructions of the application from storage308and process the instructions to generate any of the displays discussed herein. Based on the processed instructions, control circuitry304may determine what action to perform when input is received from input interface310. For example, movement of a cursor on a display up/down may be indicated by the processed instructions when input interface310indicates that an up/down button was selected.

In some embodiments, the applications are client-server based application. Data for use by a thick or thin client implemented on each one of user equipment device300and user equipment system301is retrieved on-demand by issuing requests to a server remote to each one of user equipment device300and user equipment system301. In one example of a client-server based media guidance application, control circuitry304runs a web browser that interprets web pages provided by a remote server (e.g., server404). For example, the remote server may store the instructions for the application in a storage device (e.g.,414). The remote server may process the stored instructions using circuitry (e.g., control circuitry410) and generate the displays discussed above and below. The client device may receive the displays generated by the remote server and may display the content of the displays locally on equipment device300. This way, the processing of the instructions is performed remotely by the server while the resulting displays are provided locally on equipment device300. Equipment device300may receive inputs from the user via input interface310and transmit those inputs to the remote server for processing and generating the corresponding displays. For example, equipment device300may transmit a communication to the remote server indicating that an up/down button was selected via input interface310. The remote server may process instructions in accordance with that input and generate a display of the application corresponding to the input (e.g., a display that moves a cursor up/down). The generated display is then transmitted to equipment device300for presentation to the user.

In some embodiments, the applications are downloaded and interpreted or otherwise run by an interpreter or virtual machine (run by control circuitry304). In some embodiments, the applications may be encoded in the ETV Binary Interchange Format (EBIF), received by control circuitry304as part of a suitable feed, and interpreted by a user agent running on control circuitry304. For example, the applications may be an EBIF application. In some embodiments, the content delivery application may be defined by a series of JAVA-based files that are received and run by a local virtual machine or other suitable middleware executed by control circuitry304. In some of such embodiments (e.g., those employing MPEG-2 or other digital media encoding schemes), the applications may be, for example, encoded and transmitted in an MPEG-2 object carousel with the MPEG audio and video packets of a program.

FIG. 4is a diagram of an illustrative media system, in accordance with some embodiments of the disclosure. User equipment devices408and410(such as user equipment device102) may be coupled to communication network406. Communication network406may 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. Paths (e.g., depicted as arrows connecting the respective devices to communication network406) may 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. Communications with the client devices may be provided by one or more of these communications paths, but are shown as a single path inFIG. 4to avoid overcomplicating the drawing.

System400includes media content source402and server404. Communications with the media content source402and server404may be exchanged over one or more communications paths, but are shown as a single path inFIG. 4to avoid overcomplicating the drawing. In addition, there may be more than one of each of media content source402and server404, but only one of each is shown inFIG. 4to avoid overcomplicating the drawing. If desired, media content source402and server404may be integrated as one source device.

In some embodiments, the server404may include control circuitry410and storage414(e.g., RAM, ROM, Hard Disk, Removable Disk, etc.). The server404may also include an input/output path412. I/O path412may provide device information, or other data, over a local area network (LAN) or wide area network (WAN), and/or other content and data to control circuitry410, which includes processing circuitry, and storage414. Control circuitry410may be used to send and receive commands, requests, and other suitable data using I/O path412. I/O path412may connect control circuitry304(and specifically processing circuitry) to one or more communications paths.

Control circuitry410may be based on any suitable processing circuitry such as one or more microprocessors, microcontrollers, digital signal processors, programmable logic devices, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), etc., and may include a multi-core processor (e.g., dual-core, quad-core, hexa-core, or any suitable number of cores) or supercomputer. In some embodiments, control circuitry410may be distributed across multiple separate processors or processing units, for example, multiple of the same type of processing units (e.g., two Intel Core i7 processors) or multiple different processors (e.g., an Intel Core i5 processor and an Intel Core i7 processor). In some embodiments, control circuitry410executes instructions for an emulation system application stored in memory (e.g., storage414).

Memory may be an electronic storage device provided as storage414that is part of Control circuitry410. As referred to herein, the phrase “electronic storage device” or “storage device” should be understood to mean any device for storing electronic data, computer software, or firmware, such as random-access memory, read-only memory, hard drives, solid state devices, quantum storage devices, or any other suitable fixed or removable storage devices, and/or any combination of the same. Nonvolatile memory may also be used (e.g., to launch a boot-up routine and other instructions).

Server404may retrieve guidance data from media content source402, process the data as will be described in detail below, and forward the data to the client devices408and410. Media content source402may include one or more types of content distribution equipment including a television distribution facility, cable system headend, satellite distribution facility, programming sources (e.g., television broadcasters, such as NBC, ABC, HBO, etc.), intermediate distribution facilities and/or servers, Internet providers, on-demand media servers, and other content providers. NBC is a trademark owned by the National Broadcasting Company, Inc., ABC is a trademark owned by the American Broadcasting Company, Inc., and HBO is a trademark owned by the Home Box Office, Inc. Media content source402may be the originator of content (e.g., a television broadcaster, a Webcast provider, etc.) or may not be the originator of content (e.g., an on-demand content provider, an Internet provider of content of broadcast programs for downloading, etc.). Media content source402may include cable sources, satellite providers, on-demand providers, Internet providers, over-the-top content providers, or other providers of content. Media content source402may also include a remote media server used to store different types of content (including video content selected by a user), in a location remote from any of the client devices. Systems and methods for remote storage of content and providing remotely stored content to user equipment are discussed in greater detail in connection with Ellis et al., U.S. Pat. No. 7,761,892, issued Jul. 20, 2010, which is hereby incorporated by reference herein in its entirety.

Media content source402may also provide media guidance data that can be used to create carousels and queries as described herein. Media guidance data may be provided to the client devices using any suitable approach. Program schedule data and other guidance data may be provided to the client devices on a television channel sideband, using an in-band digital signal, using an out-of-band digital signal, or by any other suitable data transmission technique.

Client 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 communication network406. In such embodiments, user equipment devices may operate in a peer-to-peer manner without communicating with a central server.

The systems and devices described inFIGS. 3 and 4enable not only display of the screens ofFIGS. 1-2, but also enable the execution of processes described inFIGS. 5-10. It should be noted that each step of processes described inFIGS. 5-10can be performed by control circuitry (e.g., in a manner instructed to control circuitry304by a content recommendation application) or any of the system components shown inFIG. 3. It should be noted that the embodiments ofFIGS. 5-10can be combined with any other embodiment in this description are not limited to the devices or control components used to illustrate the processes.

FIG. 5is a flowchart of a detailed illustrative process for timing the delivery of a content recommendation, in accordance with some embodiments of the disclosure. A main loop of process500begins at step502. At step504, a content recommendation application generates (e.g., using control circuitry410) a content recommendation. For example, the content recommendation application may identify a plurality of content items, obtain information about those items, and then calculate a predicated interest level for a user (e.g., an operator of user equipment102) for each content item. The content recommendation application may then select content deemed more interesting to that user (e.g., with a higher interest level).

At step506, the content recommendation application detects (e.g., using control circuitry410) output of a first content item. For example, the content recommendation application may obtain information indicating that a user is viewing a movie on user equipment102. That information may comprise a message received at server404via an I/O path412. Additionally, or alternatively, a content recommendation application may be executed by the control circuitry304of user equipment102. The content recommendation application may, in those embodiments, access status information for the user equipment102from storage (e.g.,308ofFIG. 3) and determine that content output is occurring on the user equipment102.

At step508, the content recommendation application determines (e.g., using control circuitry410) viewing metrics for the first content. For example, the content recommendation application may access information about a user's viewing of content104A to determine a length of time the user has been watching content104A. In some embodiments, the viewing metrics may comprise actions taken to begin watching the content (e.g., a set of menu options accessed by a user within a media guidance application such as display200). Still further, the viewing metrics may include the number of times the user has returned to watching content104A from other content.

At step510, the content recommendation application determines (e.g., using control circuitry410) whether the viewing metrics indicate that output of the content recommendation should be blocked. For example, the content recommendation application may compare how long a user has been watching content with a time threshold that indicates engagement as described with reference to process510A inFIG. 6. In some embodiments, the system may correlate the user's viewing of content104A with the user's content preferences to refine the determination of whether to block the content recommendation such as described with reference to process510B inFIG. 7.

In some embodiments, the viewing metrics may include indications of the user's actions while consuming content104A. For example, systems and methods for determining a user's engagement level with content, including the use of gaze detection, are discussed in greater detail in connection with Wheatley et al., U.S. Patent Pub. No. 2015/0189377, published Jul. 2, 2015, which is hereby incorporated by reference herein in its entirety. The content recommendation application may determine the percentage of time the user is gazing at the content104A as an indicator of whether the user is engaged with the content. If the user is not engaged with the content, as indicated because the user's gaze is not directed to the content for a threshold of the percentage of the content presentation, then the content recommendation application may determine that the content recommendation should not be blocked. In some embodiments, the content recommendation application may access the user's usage of other devices as part of the viewing metrics. For example, the user may be watching content on user equipment (e.g., user equipment410) while also using a mobile phone (e.g., user equipment408) that is in communication with the content recommendation application via a communication network (e.g., communication network406). The content recommendation application may receive information that a user is presently surfing the web while other user equipment presents content104A. This viewing metric may indicate the user is not engaged with content104A and therefore the content recommendation application should not block the content recommendation.

Process500continues to step512if the content recommendation application determines the content recommendation should be blocked. If the content recommendation application does not determine the content recommendation should be blocked, process500continues at step518. At step512, the content recommendation application (e.g., using control circuitry410) blocks the output of the content recommendation. For example, the content recommendation application may store the content recommendation into a recommendation buffer in memory and determine not to send a message containing the recommendation to user equipment102. In some embodiments, the content recommendation application may hold the content recommendation in storage of the user equipment102without presenting the content recommendation on a display312of user equipment102. Thus, the content recommendation application may, in some embodiments, prevent the generation of a content recommendation message (e.g., message110) at a content consumption device (e.g., user equipment102).

At step514, the content recommendation application detects (e.g., using control circuitry410) an input that changes the output of the first content (e.g., content104A) to a second content (e.g., content104B). In other words, the content recommendation application detects that a user is commanding user equipment (e.g., user equipment102) to display a new show. In some embodiments, the content recommendation application receives a message via communication network406from user equipment (e.g., user equipment102) that indicates the user changed a channel or selected new content in a media guidance application (e.g., display200).

At step516, the content recommendation application unblocks (e.g., using control circuitry410) the content recommendation. For example, the content recommendation application may consider the input of step514to indicate the user is no longer engaged with the content being displayed and use that change of engagement as an optimal time to deliver the content recommendation. The content recommendation application may retrieve the content recommendation from storage (e.g., from a content recommendation buffer in storage414). At step518, the content recommendation application outputs the content recommendation. For example, the content recommendation application transmits (e.g., using control circuitry410) a message to user equipment (e.g., user equipment102via communication network406) that identifies the recommended content for display to a user. In some embodiments, the content recommendation application may be executed on user equipment102and outputs the content recommendation as a message (e.g., content recommendation prompt110on user equipment102).

FIG. 6is a flowchart of a detailed illustrative process for determining whether viewing metrics indicate output of a content recommendation should be blocked, in accordance with some embodiments of the disclosure.

Process510A begins after step508ofFIG. 5. At step602, the content recommendation application retrieves (e.g., using control circuitry410) a timestamp that indicates when a device (e.g., user equipment102) began outputting the first content (e.g., content104B). For example, the user equipment102may transmit (e.g., via communication network406) a message to a server404that is executing the content recommendation application when the user equipment102begins to output content to a user. The process server404, may store a timestamp (e.g., a time noted in the message for when content output began or the time when the message was received at the server) and the content recommendation application may retrieve that timestamp from memory. Or the content recommendation application may be executed by user equipment102and the content recommendation application may store status information associated with content playback.

At step604, the content recommendation application calculates a time difference between the current time (e.g., the time at which the content recommendation application is determining whether to output a content recommendation) and the timestamp. At step606, the content recommendation application compares the time difference with a time threshold (e.g., time length) to determine whether to block the content recommendation. For example, the content recommendation application may retrieve a time threshold from memory and compare a length of time the user has watched the content104A to determine whether the user is engaged with the content. If the length of time the user has been watching the content104A exceeds this time threshold, then the content recommendation application may consider the user to be engaged with the content and determine that outputting the content recommendation would distract the user. Thus, the content recommendation application may determine the recommendation should be blocked to prevent distracting the user from being engaged with the content. In some embodiments, the time threshold is set to a percentage of the overall length of the content (e.g., 5%, 10%, or some configurable percentage). In some embodiments, the content recommendation application adjusts the time length over time in response to user action. For example, if the content recommendation application retrieves a two minute time threshold for a user that is watching content for 1:30, and the user rejects the recommendations, then the system may reduce the time threshold (e.g., by 5 seconds) in an attempt to train the time threshold to match the user's preference. Still further, a content recommendation application may analyze user access patterns across multiple users and across different content types to determine various indicators for engagement and train the time threshold to correlate with those access patterns.

FIG. 7is a flowchart of a detailed second illustrative process for determining whether viewing metrics indicate that output of a content recommendation should be blocked, in accordance with some embodiments of the disclosure.

Process510B begins after step508ofFIG. 5. At step702, the content recommendation application obtains (e.g., using control circuitry410) attributes associated with the first content item. For example, the content recommendation application may access storage (e.g., storage414) to obtain metadata about the content (e.g., genre, actors, teams, sports, players, date content first appeared, content rating, content length, number of times the content has been watched be the user).

At step704, the content recommendation application retrieves (e.g., using control circuitry410) engagement weights corresponding with the attributes. For example, the content recommendation application may provide a system of adjustment values or multipliers associated with different attributes. In some embodiments, the content recommendation application provides a user interface that allows a user to adjust the attributes a user deems more important than others and saves those weights (e.g., numerical values) in storage for use when determining engagement levels. In some embodiments, the content recommendation application monitors interactions between the user and content to train the weights to make a more accurate generation of engagement level. For example, the content recommendation application may store indications of whether a user is accepting or rejecting each content recommendation along with information about the content on the screen at the time when the user accepts or rejects the recommendation. The system may then correlate common attributes (e.g., whenever baseball is on the screen the user rejects recommendations) and adjust the corresponding weights for those attributes to more accurately predict the user's engagement level.

At step706, the content recommendation application applies (e.g., using control circuitry410) the engagement weights to the corresponding attributes. For example, the content recommendation application may determine that a first decimal value (e.g., 83.0) should be applied to the content item because it is an animation movie; a second value (e.g., 20.0) should be applied because the content contains one actor the user enjoys; and a third value (e.g., 90.0) should be applied because the content is new, and the user typically watches new content all the way through. At step708, the content recommendation application generates (e.g., using control circuitry410), using the weighted attributes, an engagement level for the first content. For example, the content recommendation application may add all the weight values together to come up with a raw score representing the engagement level or may average the weighted values to come up with the engagement level.

At step710, the content recommendation application determines (e.g., using control circuitry410) whether the engagement level indicates viewing engagement. For example, the content recommendation application may retrieve an engagement threshold from storage414to correspond with a value the content recommendation application uses to assume a user is engaged with content. The content recommendation application may retrieve a hard-coded engagement threshold, or the engagement threshold may be configurable by either a service provider or by the user. In some embodiments, the content recommendation application may adjust the engagement threshold over time—as similarly described above with the attribute weights—to more accurately depict the engagement based on user interaction. For example, if a user rejects a content recommendation, the content recommendation application may evaluate whether the threshold was set too high such that content recommendations that were being made interrupted a user's enjoyment of content and, based on the user's reactions to the content recommendation (i.e., consistent rejections), an adjustment of the threshold would be appropriate.

FIG. 8is a flowchart of a detailed illustrative process for outputting a content recommendation, in accordance with some embodiments of the disclosure.

Process518A begins after step516ofFIG. 5. At step802, the content recommendation application cancels (e.g., using control circuitry304or control circuitry410) the input to change output of the first content to output of the second content. For example, in an embodiment where some portion of the content recommendation application resides on a user equipment (e.g., user equipment102) then the content recommendation application may detect an input on user input interface (e.g.,310) that is a command to change to new content (i.e., a channel change command or command to play back content). The content recommendation application may, having detected such a command, intercept and stop the command from completing execution. In some embodiments, the content recommendation application resides on a remote server (e.g.,404), and the content recommendation application may receive a message indicating the user is changing the content. The content recommendation application, in those embodiments, may send a responsive message to user equipment (e.g., user equipment102) to cancel the input.

At step804, the content recommendation application generates (e.g., using control circuitry410), for output by a content consumption device, an option to change output of the first content to output recommended content, wherein the recommended content is identified by the content recommendation. For example, the content recommendation application generates a content recommendation prompt (e.g.,110) on a display (e.g.,312). In some embodiments, generating the content recommendation prompt may comprise building a message that is transmitted to a user equipment (e.g.,102) for display to the user.

At step806, the content recommendation application (e.g., using control circuitry410) receives a selection of the option to change output of the first content to output of the recommended content. For example, the content recommendation application may receive a selection of an option to accept the recommended content (e.g., option116) or an option to reject the recommended content (e.g., option118).

At step808, the content recommendation application (e.g., using control circuitry410) generates, for output by the content consumption device, the recommended content. For example, a remote server404may direct a stream of the recommend content to a user equipment (e.g.,102). In some embodiments, the content recommendation application resides on a user equipment (e.g.,102) and the content recommendation application begins outputting the recommended content on a display (e.g.,312).

FIG. 9is a flowchart of a detailed second illustrative process for outputting a content recommendation, in accordance with some embodiments of the disclosure.

Process518B begins after step516ofFIG. 5. At step902, the content recommendation application generates (e.g., using control circuitry410), for output by a content consumption device, the second content. For example, a user equipment102begins outputting the second content on a display (e.g.,312). At step904, the content recommendation application generates (e.g., using control circuitry410), for output by the content consumption device (e.g., user equipment102), an option to change output of the second content to output of recommended content, wherein the recommended content is identified by the content recommendation. For example, in an embodiment where some portion of the content recommendation application resides on a user equipment (e.g., user equipment102) then the content recommendation application may detect an input on user input interface (e.g.,310) that is a command to change to new content (i.e., a channel change command or command to play back content). The content recommendation application may, having detected such a command, intercept and stop the command from completing execution. In some embodiments, the content recommendation application resides a remote server (e.g.,404) and the content recommendation application may receive a message indicating the user is changing the content. The content recommendation application, in those embodiments, may send a responsive message to user equipment (e.g., user equipment102) to cancel the input.

At step906, the content recommendation application receives (e.g., using control circuitry410) a selection of the option to change output of the second content to output of the recommended content. For example, the content recommendation application may receive a selection of an option to accept the recommended content (e.g., option116) or an option to reject the recommended content (e.g., option118).

At step908, the content recommendation application (e.g., using control circuitry410) generates, for output by the content consumption device, the recommended content. For example, a remote server404may direct a stream of the recommend content to a user equipment (e.g.,102). In some embodiments, the content recommendation application resides on a user equipment (e.g.,102), and the content recommendation application begins outputting the recommended content on a display (e.g.,312).

FIG. 10is a flowchart of a detailed illustrative process for determining a content recommendation, in accordance with some embodiments of the disclosure. At step1002, the content recommendation application identifies (e.g., using control circuitry410) a plurality of content items. For example, the content recommendation application may access storage (e.g.,414) and obtain a listing of potential content items (e.g., a listing of live content items). At step1004, the content recommendation application obtains (e.g., using control circuitry410) information about the content items. For example, the content recommendation application may obtain metadata about the content or analyze the content to retrieve details about the content (e.g., information about what happens in the content or the current status of the content). In the case where content items correspond with real-life events, the content recommendation application may obtain status and data about the real-life event (e.g., a sports game).

The content recommendation application may retrieve information specific to the content item or information that applies to the content item but is also general enough to apply to other content items as well. For example, the content recommendation application may obtain the time in a season that a sporting event is occurring (e.g., preseason, week one, week four, playoffs, championship), the relative ranking of competitors in the competition (e.g., rank one versus rank two), a current score between teams participating in a live sporting event, a scoring frequency indicator for a live sporting event (e.g., an indicator of how often the score is changing), an amount of time remaining in a live sporting event, or a number of viewers associated with the content item. Still other information pertaining to a content item may be used to determine a predicted interest level for a content item.

At step1006, the content recommendation application calculates (e.g., using control circuitry410), based on the information about the content, interest levels for the plurality of content items. Users may have different interests and the content recommendation application may dynamically calculate projected user interest for all content (e.g., live sports programming). The content recommendation application may allow a user to set their threshold for notification (e.g., 1 through 1000). If the user set a threshold of 300, then the content recommendation application will not notify the user unless the predicted interest for a piece of content exceeds that threshold (e.g., 300). The content recommendation application would likely calculate a different predicted interest level for each individual user. In some embodiments, the content recommendation application calculates interest levels for the plurality of content items in accordance with steps1020-1026ofFIG. 10. At step1020, the content recommendation application obtains (e.g., using control circuitry410) content preferences. For example, the content recommendation application may obtain preferences related to a user for the type of content and status of the content. At step1022, the content recommendation application generates (e.g., using control circuitry410) weighting values, based on the content preferences, for one or more attributes in the information about the content. For example, the content recommendation application may determine that the user has a preference for close games in the late stages. Thus, an attribute of a baseball game indicating it is in the ninth inning may be weighted heavily (e.g., with a score of 90) and an attribute indicating the score of the same game is within 2 runs may also be weighted heavily (e.g., with a score of 80). At step1024, the content recommendation application sums (e.g., using control circuitry410) the weighting values for a plurality of attributes associated with the content items. At step1026, the content recommendation application assigns (e.g., using control circuitry410) the sums of the weighting values for each of the content items to the corresponding content item.

At step1008, the content recommendation application selects (e.g., using control circuitry410), based on the interest levels for the plurality of content items, recommended content from the plurality of content items. For example, the content recommendation application accesses a list of calculated interest levels for content and determines which interest level is calculated higher than the others. In some embodiments, the content recommendation application also determines whether the calculated interest levels exceed a threshold level retrieved from storage (e.g.,414).

At step1010, the content recommendation application receives (e.g., using control circuitry410) an update to the information about the content. For example, the status of a sports game, or other real-life event, may change as time progress (e.g., a score change, the amount of time remaining, the number of people watching the game). The content recommendation application may access an information source, e.g., a data source such as media content source402, to retrieve those updates. At step1012, the content recommendation application recalculates (e.g., using control circuitry410), based on the updated information about the content, updated interest levels for the plurality of content items. At step1014, the content recommendation application updates (e.g., using control circuitry410), based on the updated interest levels for the plurality of content items, the recommended content. For example, the content recommendation application may change a content recommendation from a first recommended content item (e.g., a baseball game such as content104C) to a second recommended content item (e.g., a hockey game) based on a second interest level for the second recommend content item rising above a first interest level for the first recommended content item.

In some embodiments, the content recommendation application may modify the calculation used to generate the interest levels based on whether a user accepts or rejects the content recommendation. For example, at step1016, the content recommendation application receives (e.g., using control circuitry410), from a content consumption device, an indication that the content recommendation was rejected. At step1018, the content recommendation application modifies (e.g., using control circuitry410), based on receiving the indication that the content recommendation was rejected, the calculation of interest levels for the plurality of content items, wherein the modification of the calculation is performed to lower a calculated interest level for recommended content corresponding with the content recommendation. For example, the content recommendation application would provide the content recommendations to each user, based on information relevant to that user. When the user accepts a content recommendation (i.e., switches to the recommended content) the content recommendation application may reinforce the calculation of the predicted interest level by, e.g., increasing the weighting of the factors. If the user rejects the content recommendation, the content recommendation application may reduce the calculated interest level by, e.g., decreasing the weighting of factors.