Patent Document

BACKGROUND  
       [0001]    Today&#39;s online advertising ecosystem is driven by the ubiquitous tracking of end users&#39; engagement with websites and services. Advertisements are selected to match an end user&#39;s interests based on profiles mined by tracking services. One feature of such existing systems is that end users, the presumed beneficiaries, have little control over the data that is collected by such tracking services, or how such data is targeted. While some tracking services expose a user&#39;s profile and allow it to be edited, a majority of such tracking services do not do so, and little is known about how such tracking services operate. And even in systems where a user&#39;s profile is exposed, such systems do not allow the user to reason about why they are being presented with a particular advertisement. 
       SUMMARY  
       [0002]    A method is provided for enabling greater transparency by allowing a user to reason about a particular advertisement displayed on a web page he or she is visiting. The method also grants users fine grained control wherein they can suppress advertisements targeting a particular category. 
         [0003]    The method includes detecting whether an advertisement is a contextual advertisement; detecting whether the advertisement is a retargeted advertisement; and detecting whether the advertisement is a behaviorally targeted advertisement. The detecting whether the advertisement is a contextual advertisement includes disabling an identifying profile associated with the user; browsing the web page on which the advertisement was embedded while the identifying profile is disabled; and determining whether the advertisement is presented on the web page while the identifying profile is disabled. The detecting whether the advertisement is a retargeted advertisement includes identifying one or more previously visited web pages, the previously-visited web pages having a domain associated therewith; and determining whether a domain associated with the advertisement matches one of the domains associated with the one or more previously-visited web pages. The detecting whether the advertisement is a behaviorally targeted advertisement includes determining that the advertisement is not a contextual advertisement and is not a retargeted advertisement. 
         [0004]    Also disclosed is a method of suppressing classified advertisements on a web page. The method includes identifying one or more previously-visited web pages, which were visited prior to encountering an advertisement on a current web page; visiting the one or more web pages chronologically; identifying one or more target web pages from the one or more web pages, the one or more target web pages having a content association that is a same content association had by the advertisement; skipping the one or more target web pages in chronology; and saving a resultant click stream associated with the visiting of the one or more previously visited web pages while skipping the one or more target web pages. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS  
         [0005]    For a more complete understanding of the present invention, reference is made to the following detailed description of an embodiment considered in conjunction with the accompanying drawings, in which: 
           [0006]      FIG. 1  is a diagram of a system configured to perform web advertisement classification and suppression in accordance with an embodiment of the present invention; 
           [0007]      FIG. 2  is a flow chart showing a method of classifying web advertisements in accordance with an embodiment of the present invention; 
           [0008]      FIG. 3   a  is a flow chart showing a method of suppressing classified advertisements in accordance with an embodiment of the present invention; and 
           [0009]      FIG. 3   b  is a flow chart showing a method of suppressing classified advertisements in accordance with another embodiment of the present invention. 
       
    
    
     DETAILED DESCRIPTION  
       [0010]    The present disclosure relates to a platform for allowing users to identify and control the advertisements appearing on their Internet web browsers. The platform enables greater transparency with respect to advertisements by allowing users to learn what elements of their Internet browsing led to the display of the advertisement in question. The platform also allows users to suppress advertisements of a particular category, rather than an all-or-nothing approach, thereby giving users fine-grained control over the advertisements they see while browsing the Internet. 
         [0011]    It should be understood that the elements shown in the figures may be implemented in various forms of hardware, software or combinations thereof. Preferably, these elements are implemented in a combination of hardware and software on one or more appropriately programmed general-purpose devices, which may include a processor, memory and input/output interfaces. Other elements can be implemented through the use of specifically-purposed devices, such as electronic display screens and audio-visual devices. 
         [0012]      FIG. 1  illustrates a platform  100  constructed in accordance with an embodiment of the present invention. The platform includes two logical components: a client side  102  that monitors web transactions conducted by a user  104  and filters outgoing HTTP connections, and a backend  106  for analyzing web pages visited by the user and performing detailed characterizations of the web pages and the advertisements thereon. The client side  102  includes an advertisement control interface  108  to allow the user to execute the methods disclosed further below. The backend  106  includes a memory  110  for storing a user&#39;s browsing history and control preferences, which are associated with the user&#39;s profile, and a Universal Resource Locator (URL) classification engine  112  for investigating and classifying advertisements according to subject matter, such as, for example, “Loans→Mortgage” or “Recreation→Children&#39;s Toys.” The backend  106  also includes an advertisement classifier  114 , which is configured to execute a number of processes for classifying an advertisement&#39;s type, such as, for example, contextual, retargeting, and behavioral. These processes are discussed in detail further below. 
         [0013]      FIG. 2  illustrates a method  200  of classifying web advertisements in accordance with an embodiment of the present invention. The method begins when a user visits a web page (step  202 ) and is presented with an advertisement that the user  104  would like to investigate. The user initiates an identification procedure (step  204 ) on the advertisement. In one embodiment, the identification procedure  204  is deliberately activated by the user  104  through the use of a plugin. In another embodiment, the identification procedure (step  204 ) activates upon view of an advertisement without direction from the user  104 . 
         [0014]    Upon activation of the identification procedure, the advertisement classifier  114  tests whether the advertisement is a contextual advertisement, a re-targeting advertisement, or a behavioral advertisement. The advertisement classifier  114  begins by attempting to find the same advertisement that the user sees while browsing the web page without any identifying profile (step  206 ). In one embodiment, this test is performed K times consecutively. If the same advertisement is found at least once out of the K attempts, the advertisement classifier  114  determines that the advertisement is contextual and labels it as such (step  208 ). 
         [0015]    If the advertisement classifier  114  determines that the advertisement is not contextual, it compares the domain of the web page embedding the advertisement with the domains of previously-visited web pages associated with the advertisement&#39;s ad-network or tracker (step  210 ). If a match exists between the domain of the embedded advertisement and one of the domains of the previously-visited web pages, the advertisement classifier  114  determines that the advertisement is re-targeted and labels it as such (step  212 ). If no match is found, the advertisement is assumed to result from behavioral targeting, and is thus labeled as behavioral (step  214 ). 
         [0016]    In one embodiment, the advertisement classifier  114  indicates a category or associated subject matter, such as, for example, “Loans→Mortgage” or “Recreation→Children&#39;s Toys,” for an advertisement classified as behavioral. In one embodiment, the advertisement classifier  114  also provides to the user a link for “more information,” which leads the user to a page displaying the web pages in the user&#39;s history that are categorized with the same category associated with the advertisement in question. 
         [0017]      FIGS. 3   a  and  3   b  illustrate various methods  300   a,    300   b  of suppressing advertisements from their particular category in accordance with embodiments of the present invention. With reference to  FIG. 3   a , in one embodiment with respect to suppressing behaviorally targeted advertisements, the advertisement classifier  114  identifies all web pages visited by the user up until the time the behaviorally targeted advertisement in question is encountered (step  302 ). The advertisement classifier  114  then visits these web pages in chronological order until it reaches a web page whose category matches the category of the behaviorally targeted advertisement (step  304 ). Any such web page is then skipped over (step  306 ), thereby avoiding the behavior associated with the behaviorally targeted advertisement. This process continues until the advertisement classifier  114  reaches the web page currently viewed by the user (step  308 ). The resultant click stream is then stored in a cookie for future use (step  310 ). A “click stream” is a term of art relating to data that represents selections or “clicks” by a user. 
         [0018]    With reference to  FIG. 3   b , in one embodiment with respect to re-targeted advertisements, the advertisement classifier  114  identifies web pages visited by the user up until the time the retargeted advertisement in question is encountered (step  312 ). The advertisement classifier  114  then visits these web pages in chronological order until it reaches a web page whose domain matches the domain of the retargeted advertisement (step  314 ). Any such web page is then skipped over (step  316 ), thereby avoiding the original visit to the domain in question that resulted in the retargeted advertisement. This process continues until the advertisement classifier  114  reaches the web page currently viewed by the user (step  318 ). The resultant click stream is then stored in a cookie for future use (step  320 ). 
         [0019]    To ensure that these user preferences are maintained, one embodiment of the present invention includes employing an online page classifier to block cookies from pages associated with the category that the user wishes to block. In one embodiment, the advertisement classifier  114  first allows only HTTP requests from the main body of the page to pass through to the user while blocking advertisement-related HTTP requests. The advertisement classifier  114  then scans the page category of advertisement-related HTTP requests and allows those which the user has not specifically chosen to avoid to pass through to the user. In this embodiment, HTTP requests whose categories match those categories associated with the saved cookies generated from the processes illustrated in  FIGS. 3   a  and  3   b  are blocked until the user chooses to unblock them. 
         [0020]    The various embodiments disclosed herein can be implemented as hardware, firmware, software, or any combination thereof. Moreover, the software is preferably implemented as an application program tangibly embodied on a program storage unit or computer readable medium. The application program may be uploaded to, and executed by, a machine comprising any suitable architecture. Preferably, the machine is implemented on a computer platform having hardware such as one or more central processing units (“CPUs”), a memory, and input/output interfaces. The computer platform may also include an operating system and microinstruction code. The various processes and functions described herein may be either part of the microinstruction code or part of the application program, or any combination thereof, which may be executed by a CPU, whether or not such computer or processor is explicitly shown. 
         [0021]    All examples and conditional language recited herein are intended for pedagogical purposes to aid the reader in understanding the principles of the invention and the concepts contributed by the inventor to furthering the art, and are to be construed as being without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, and embodiments of the invention, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents as well as equivalents developed in the future, i.e., any elements developed that perform the same function, regardless of structure. 
         [0022]    It will be understood that the embodiments described herein are merely exemplary and that a person skilled in the art may make many variations and modifications without departing from the spirit and scope of the invention. All such variations and modifications are intended to be included within the scope of the invention as defined in the appended claims.

Technology Category: h