Patent Publication Number: US-11386450-B2

Title: Systems and methods for advertising on content-screened web pages

Description:
RELATED APPLICATION(S) 
     This application is a continuation of and claims the benefit of priority to U.S. Nonprovisional application Ser. No. 14/247,178, filed on Apr. 7, 2014, which is a continuation of and claims the benefit of priority to U.S. Nonprovisional application Ser. No. 12/612,270, filed on Nov. 4, 2009, now U.S. Pat. No. 8,712,847, issued Apr. 29, 2014, which claims the benefit of priority of provisional patent application No. 61/111,624, filed on Nov. 5, 2008, by Eric Bosco, et al., each of which is incorporated by reference herein in its entirety. 
    
    
     TECHNICAL FIELD 
     The present disclosure relates generally to systems and methods for advertising on web pages. More particularly, and without limitation, the present disclosure relates to systems and methods for rating the content of a web page and delivering advertising to the web page based on the content rating. 
     BACKGROUND 
     Since the early 1990&#39;s, the number of people using the World Wide Web has grown at a substantial rate. As more users take advantage of the World Wide Web, higher volumes of traffic are generated over the Internet. Because the benefits of commercializing the Internet to take advantage of these higher traffic volumes can be tremendous, businesses increasingly seek means to advertise their products or services on-line. These advertisements may appear, for example, in the form of leased advertising space (e.g., “banners”) on websites or as advertisements presented to digital television users, which are comparable to rented billboard space or to commercials broadcasted during television or radio programs. 
     When a company advertises on a website, it may benefit from the volume of advertisements or impressions that it places on the website, the number of users that select or “click” on each advertisement, and the number of sales or other “conversions” that result from each display of an advertisement. Each instance that an advertisement is placed on a web page may be referred to as an “impression.” Companies may pay per impression, per click, and/or per conversion. As a result, it may be advantageous for advertisers to increase the number of web pages on which companies may display advertisements. 
     Traditionally, advertising services acquired an inventory of empty ad space on particular known web sites, such as news sites and commerce sites, which could then be offered to companies based on the desirability of advertising on the particular web site. Recently, there has been a significant increase in the quantity of user-generated content (“UGC”) sites, on which a large proportion of the site&#39;s content is created and posted by users, rather than administrators or professional contributors. For example, there has been a significant increase in social networking sites, blogs, review sites, file sharing sites, and personal opinion sites. Because these sites are growing in number and drawing more web traffic, it is becoming more desirable to advertise on these sites. However, many advertisers are hesitant to have ad networks display their ads on UGC sites that could have offensive or objectionable material posted thereon by users. For example, a children&#39;s media provider may desire to display ads on a high-traffic, house pet-related MySpace page, but not on a high-traffic, gambling-related MySpace page. In the past, advertising services have been unable to distinguish between particular pages of a web site (e.g., between two different pages on MySpace.com), when offering ad inventory to content-sensitive advertisers. 
     The present disclosure is directed to increasing the amount of advertising on web sites by solving one or more of the above-mentioned challenges. 
     SUMMARY 
     In accordance with one exemplary embodiment, the present disclosure is directed to a method for advertising on a content-screened web page. The method includes receiving an impression request for a URL for which an advertising impression is desired; screening HTML content of a web page identified by the URL; generating a rating for the URL based on the screened HTML content of the web page; assigning the rating to the impression request; and serving an advertising impression on the web page based on the rating. 
     In accordance with another exemplary embodiment, the present disclosure is directed to a method for delivering advertising to a publisher of a content site. The method includes receiving an impression request from a publisher of a content site on which an advertising impression is desired; generating a rating for the content site based on HTML content of the content site; appending the rating to the impression request; and sending the impression request and rating to an ad server. 
     In accordance with another exemplary embodiment, the present disclosure is directed to a method for delivering advertising to a publisher of a content site. The method includes receiving an impression request from a publisher of a content site on which an advertising impression is desired; appending an existing rating to the impression request if a rating for the content site is stored in a response cache; adding a URL for the content site to a request queue if a rating for the content site is not stored in the response cache; generating a new rating for the content site based on HTML of the content site if a rating for the content site is not stored in the response cache; and appending the new rating to the impression request once it is generated. 
     Additional features and advantages will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the embodiments of the invention. For example, the features and advantages may be realized and attained by means of the elements and combinations particularly pointed out in the appended claims. 
     It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate several embodiments of the invention and together with the description, serve to explain the principles of the invention. 
         FIG. 1  shows a block diagram of an exemplary network for placing advertising on content-screened web pages; 
         FIG. 2  shows a block diagram of an exemplary architecture for placing advertising on content-screened web pages; and 
         FIG. 3  illustrates an exemplary method for placing advertising on content-screened web pages, using the exemplary network of  FIG. 1  and architecture of  FIG. 2 . 
     
    
    
     DESCRIPTION OF THE EMBODIMENTS 
     Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts. 
       FIG. 1  illustrates an exemplary content screening network  100  for placing advertising on content-screened web pages. Network  100  may include a plurality of users  102 , advertisers  104 , publishers  106 , ad servers  108 , and a content screening service  110 , all disposed in communication with the Internet  101 . As will be described in more detail below, in certain embodiments, network  100  may be configured to receive advertisements from advertisers  104 , rate web pages hosted by publishers  106  using content screening service  110 , and instruct ad servers  108  to deliver the advertisements on web pages of various publishers  106 , based on the ratings generated by content screening service  110 . 
     Advertisers  102  may include any entities having online advertisements (e.g., banner ads, pop-ups, etc.) desired to be delivered to online users. For example, advertisers  102  may have created advertisements relating to products or services marketable to one or more online users. Advertisers  102  may interact with publishers  106 , ad servers  108 , and/or content screening service  110  through computers connected to the Internet  101 . Thus, advertisers  104  may be able to communicate advertising campaign information, such as ad information, targeting information, consumer information, budget information, bidding information, etc., to other entities in network  100 . 
     Publishers  106  may include any entities having inventories of available online advertising space. For example, publishers  106  may include online content providers, search engines, e-mail programs, or any other online site or program having online user traffic. In one embodiment, publishers  106  may host user generated content (UGC) sites, such as social networking sites, blogs, review sites, file sharing sites, and personal opinion sites. Publishers  106  may interact with advertisers  104 , ad servers  108 , and/or content screening service  110  via computers connected to the Internet  101 . Thus, publishers  106  may be able to communicate inventory information, such as site information, demographic information, cost information, etc., to other entities in network  100 . 
     Ad servers  108  may include any type of servers configured to process advertising information from advertisers  104  and/or site information from publishers  106 , either directly or indirectly. In certain embodiments, ad servers  108  may be remote web servers that receive advertising information from advertisers  104  and serve ads to be placed by publishers  106 . Ad servers  108  may be configured to serve ads across various domains of publishers  106 , for example, based on advertising information provided by advertisers  104 . Ad servers  108  may also be configured to serve ads based on contextual targeting of web sites, search results, user profile information, and/or web page ratings generated by content screening service  110 . Ad servers  108  may also be configured to generate behavioral logs, leadback logs, click logs, action logs, and impression logs, based on users&#39; interactions with web sites and ads implemented by network  100 . 
     Network  100  may also include a plurality of users  102  provided in communication with the Internet  101  and able to visit web pages hosted by publishers  106 . The term “user,” “customer,” or “person,” as used herein, may refer to any consumer, viewer, or visitor of a Web page or site and can also refer to the aggregation of individual customers into certain groupings. References to customers “viewing” ads is meant to include any presentation, whether visual, aural, or a combination thereof. 
     In one embodiment, content screening service  110  may include a plurality of app tier servers  112 , a plurality of web tier servers  114 , a plurality of response cache servers  116 , a plurality of request queue servers  118 , and a plurality of content categorization service (CCS) servers  120 . Each of the app tier servers  112  and web tier servers  114  may include a public side that interfaces with the Internet  101 , separated by a firewall from a private side that interfaces with other components of content screening service  110 . In one embodiment, request queue servers  118  may be disposed in communication with the private sides of app tier servers  112  and web tier servers  114 . Likewise, response cache servers  116  may be disposed in communication with the private sides of app tier servers  112  and web tier servers  114 . CCS servers  120  may be disposed in communication with the private side of app tier servers  112 . These components of content screening service  110  may be configured to receive advertising impression requests from publishers  106 , rate or otherwise analyze a web page associated with the impression request, and instruct ad servers  108  to serve ads on the web page based on any ratings generated by content screening service  110 . 
       FIG. 2  shows a block diagram of an exemplary architecture  200  for placing advertising on content-screened web pages using content screening service  110  of  FIG. 1 . In general, architecture  200  may operate on one or more servers described with respect to content screening service  110 , in any desired combination or configuration. For instance, in one embodiment, web tier  202  may run on web tier servers  114 , application tier  203  may run on app tier servers  112 , CCS engine  204  may run on CCS servers  120 , response cache  206  may reside on response cache servers  116 , and request queue  208  may reside on request queue servers  118 . Of course, any other suitable combinations or configurations of software and/or hardware may be implemented, as will now be appreciated by one of skill in the art. 
     In one embodiment, architecture  200  may include web tier  202  provided in communication with application tier  203  and content categorization service (“CCS”) engine  204 . Web tier  202  may be configured to receive impression requests from publishers  106  through the Internet  101 . Specifically, when one of users  102  visits a web page hosted by one of publishers  106 , that publisher  106  may send an impression request to one of ad servers  108 , requesting a suitable banner ad to serve on the visiting user  102 . Web tier  202  may be configured to intercept each impression request, check an associated web page URL against other URLs stored in response cache  206 , and send the associated web page URL to request queue  208  to be processed by app tier  203  and rated by CCS engine  204 , as will be described in more detail below. 
     CCS engine  204  may be configured to generate ratings for a URL of a web page based on the content of the web page. Web tier  202  and application tier  203  may be in communication with response cache  206 , which is configured to store URL ratings generated by CCS engine  204 . Response cache  206  may be a distributed cache disposed across numerous data storage devices and configured to store millions of web page ratings. Web tier  202  and application tier  203  may also be in communication with request queue  208 , which is configured to store URL screening requests generated by web tier  202 . Request queue  208  may be a reference counting queue configured to determine how many times each URL has been referred by web tier  202 . Thus, web tier  202  may be configured to receive impression requests from a web site, and then send the URL of the web site to either the request queue  208  or an ad server  108 , depending on whether the URL has already been screened, ranked, and stored in response cache  206  by application tier  203  and CCS engine  204 . Ad server  108  may be configured to generate either an objectionable site ID or a non-objectionable site ID, based on the content of the web page, as determined by CCS engine  204 . Skilled artisans will now appreciate that certain components of  FIG. 2  may be combined, rearranged, or omitted without departing from the spirit and scope of the invention. 
     The operation of network  100  and architecture  200  will be described in greater detail with respect to  FIG. 3 , which depicts an exemplary method  300  for placing advertising on content-screened web pages. Method  300  includes receiving an impression request from a referring URL ( 302 ) and sending the impression request to web tier  202  ( 304 ). Web tier  202  determines whether the referring URL is rated and stored in response cache  206  (step  306 ). For example, web tier  202  may extract a document referring address (“DREF”) parameter embedded in the impression request and use it as a key to look up the URL in response cache  206 . If the referring URL is rated and stored in response cache  206 , then web tier  202  appends the URL rating to the impression request ( 308 ). Web tier  202  then sends the impression request and rating to ad server  108  ( 310 ). Ad server  108  then serves an ad on the referring URL based on the rating ( 312 ), as will be described in greater detail below. 
     If the referring URL is not rated and stored in response cache  206  (step  306 , No), then web tier  202  adds the referring URL (e.g., the DREF parameter) to request queue  208  ( 314 ). Web tier  202  then sends the impression request to ad server  108  for delivery using standard ad delivery parameters ( 318 ). Ad server  108  then serves a standard ad on the referring URL ( 320 ) by, for example, serving an ad from a company that is not sensitive to the content of the web page. 
     Because request queue  208  may be a reference counting queue, request queue  208  may determine how many times each URL is referred by web tier  202 . Request queue  208  may also store a threshold value which defines how many times a URL is referred by web tier  202  before it is rated by CCS engine  204 . For example, because screening and rating may be a time and resource intensive process, it may be desirable to only screen and rate web pages that receive a certain level of web traffic. Thus, request queue  208  can be configured to determine, asynchronously, and/or upon each request, whether a threshold number of requests for that URL (e.g., 100 times, or 1000 times) has been exceeded ( 316 ). In one embodiment, application tier  203  repeatedly queries request queue  208  to determine whether a threshold number of requests has been exceeded. Application tier  203  may query request queue  208  at configurable predetermined intervals. 
     If the referring URL has been requested more than the threshold number of requests, then application tier  203  retrieves web content of the referring URL from the Internet, and sends it to CCS engine  204  to be screened and rated ( 322 ). CCS engine  204  screens and rates the content of the referring URL, and then application tier  203  places the URL and its rating in response cache  206 , where it may now be accessed by web tier  202  any time it is subsequently requested ( 324 ). In an embodiment in which CCS engine  204  screens and rates the content of the referring URL within an acceptable amount of time, the URL rating may be appended to the very same impression request that caused the URL to exceed the request queue threshold and to initiate CCS screening and rating ( 308 ). Then, web tier  202  sends the impression request and rating to ad server  108  ( 310 ). Ad server  108  then serves an ad on the referring URL based on the rating ( 312 ). 
     In order to screen and rate web pages, CCS engine  204  either fetches the raw HTML of the referring URL from the Internet, or receives it from application tier  203 , which retrieves it from the Internet  101 . CCS engine  204  then parses each word, image file, audio file, and/or video file associated with the URL for the purposes of categorizing the URL. In one embodiment, CCS engine  204  rates each URL in relation to four objectionable categories: pornographic sites, hate sites, weapons-related sites, and drug-related sites. For example, CCS engine  204  may give each URL a “yes” or “no” rating for each of the four objectionable categories. Alternatively, CCS engine  204  may assign each URL a numerical value between 0 and 1 for each of the four objectionable categories. Of course, it is contemplated that any type and number of categories may be implemented within the scope of the systems and methods of this disclosure. For example, CCS engine  204  may be configured to determine and rate the particular interest and sentiment of each URL for the purpose of achieving more targeted ad delivery, such as serving sports-related ads on the personal profiles of users exhibiting a strong interest in sports. 
     In one embodiment, CCS engine  204  extracts words out of a formatted web page in order to generate a list of features associated with the web page. CCS engine  204  then removes “stop words” (e.g., “about”, “all”, “and”, “are”, “as”. “at”, “back”, “because”, etc.) from the list of features to reduce the number of features that do not contribute to identifying content and rating the URL within various categories. CCS engine  204  then determines the occurrence frequency of each feature in the URL and generates one or more category ratings based on known web pages and ratings that it has been trained to replicate. In one embodiment, CCS engine  204  implements content identification and categorization methods similar to those used for e-mail SPAM filters and/or parental control systems. CCS engine  204  may also be configured to overcome intentional misspellings, which may be more common among user-generated content sites than traditional sites. For example, CCS engine  204  may be trained to recognize words as “hate” words even if certain letters are omitted or replaced with other letters, numbers, or symbols. Moreover, CCS engine  204  may be configured to detect and categorize expressive language (e.g., “boringggggg”) to determine the overall sentiment of a URL, for example, as either “positive” or “negative” in tone. CCS engine  204  may also use feature expansion methods which expand each feature into other related known words by implementing various methods, such as: (1) mapping (e.g., converting the feature “S3X” to “SEX”); (2) stemming (e.g., associating “ammunition”, “ammunitions”, and “munitions” with the feature “ammo”); and (3) thesaurus matching (e.g., matching “hate” to the feature “loath”). CCS engine  204  may implement any other language detection, pattern recognition, image categorization, or file parsing methods which may be useful for categorizing and rating a URL for purposes of controlling ad delivery. 
     In this manner, the systems and methods disclosed herein may be configured to deliver advertising to publishers of user generated content sites based on the content of those sites. As a result, advertisers may have their advertisements delivered to a more diverse array of inventory on the Internet, and ad networks may increase the amount of revenue earned by selling online ad inventory. Moreover, the screening and categorization techniques disclosed herein may improve the targeted delivery of advertising to content pages based on comparative analysis of characteristics of the advertiser, the advertisement, the web page, and/or the publisher. 
     It will be apparent to those skilled in the art that various modifications and variations can be made in the system and method for reception in communication networks. It is intended that the standard and examples be considered as exemplary only, with a true scope of the disclosed embodiments being indicated by the following claims and their equivalents.