| Patent application number | Description | Published |
|---|
| 20090157646 | MITIGATION OF SEARCH ENGINE HIJACKING - The subject matter disclosed herein relates to mitigation of search engine hijacking. | 06-18-2009 |
| 20090164400 | Social Behavior Analysis and Inferring Social Networks for a Recommendation System - Systems and methods are provided for determining items or people of potential interest to recommend to users in a computer-based network. Implied social networks may be determined based at least in part on obtained social behavior information. Items or people of potential interest to users may be determined based at least in part on implied social network information. Vocabulary taxonomies may be associated with, or used in determining, implied social networks. | 06-25-2009 |
| 20090248514 | SYSTEM AND METHOD FOR DETECTING THE SENSITIVITY OF WEB PAGE CONTENT FOR SERVING ADVERTISEMENTS IN ONLINE ADVERTISING - An improved system and method for detecting the sensitivity of web page content for serving advertisements in online advertising is provided. A web page sensitivity classifier may be provided for identifying the sensitivity of the content of a web page to an advertisement. The web page sensitivity classifier may use the features of a web page and the features of each advertisement in a list of candidate advertisements to identify advertisements that do not match the sensitivity of the content of the web page. Any advertisements that do not match the sensitivity of the content of the web page may be removed form the list of candidate advertisements. Web page placements may be allocated for advertisements from the list of candidate advertisements that match the sensitivity of the content of the web page, and the advertisements may be served for display. | 10-01-2009 |
| 20090327168 | PLAYFUL INCENTIVE FOR LABELING CONTENT - Embodiments are directed towards employing a playful incentive to encourage users to provide feedback that is useable to train a classifier. The classifier being associated with any of a variety of different settings, including but not limited to classifying: messages as ham/spam, images, advertising, bookmarking, music, videos, photographs, shopping, or the like. An animated image, such as a pet, provides an interface to the classifier that encourages and responds to user feedback. Users may share their classifiers or aspects thereof with other users to enable a community of knowledge to be applied to a classification task, while preserving privacy of the user feedback. One form of sharing may be within the context of a competitive game. Various evaluations may be performed on a classifier to indicate user feedback consistency, or quality. Classifiers may also be used to provide users with advertisements, products, or services based on the user's feedback. | 12-31-2009 |
| 20100010982 | WEB CONTENT CHARACTERIZATION BASED ON SEMANTIC FOLKSONOMIES ASSOCIATED WITH USER GENERATED CONTENT - The present invention is directed towards a method and system for characterizing web content based on capturing semantics of folksonomies relating to content entities of user generated content. The method and system includes determining a plurality of tags that describe a plurality of content entities and determining a co-occurrence of the tags. The method and system further includes generating weighted vectors based on the determined co-occurrence of tags and characterizing the content entity based on the weight vectors. Thereby, the characterization of the content entity may be used for any number of suitable purposes, including, by way of example, improving search results and associated advertising relevancy. | 01-14-2010 |
| 20100106704 | CROSS-LINGUAL QUERY CLASSIFICATION - The subject matter disclosed herein relates to cross-lingual query classification. | 04-29-2010 |
| 20100161605 | CONTEXT TRANSFER IN SEARCH ADVERTISING - A computer-implemented method is disclosed for determining a type of landing page to which to transfer web searchers that enter a particular query, the method comprising: classifying a landing page as one of a plurality of landing page classes with a trained classifier of a computer based on textual content of the landing page; determining, by the computer, characteristics of one or more query to be associated with the landing page; and choosing, with the computer, whether to retain or to change classification of the landing page to be associated with the one or more query based on relative average conversion rates of advertisements on a plurality of manually-classified landing pages when associated with the characteristics of the one or more query. | 06-24-2010 |
| 20110060746 | MATCHING REVIEWS TO OBJECTS USING A LANGUAGE MODEL - A method is provided to associate reviews that have unknown correspondences to tangible entities to structured objects that have known correspondences to tangible entities comprising: transforming a respective review and text from a respective structured object to a collection of words that intersect the respective review and text from the respective structured object; determining a measure of a likelihood of a match as a function of respective probabilities of occurrences of respective words of such intersecting collection within generic review text and respective probabilities of occurrences of respective words of such intersecting collection within structured object text. | 03-10-2011 |
| 20110099192 | Translation Model and Method for Matching Reviews to Objects - Disclosed are methods and apparatus for matching sets of text to objects are disclosed. In accordance with one embodiment, a set of text is obtained. For instance, the set of text may include a review. A numerical value is determined for each of a plurality of objects, where the numerical value indicates a likelihood that the corresponding one of the plurality of objects is a subject of the set of text. Each of the plurality of objects has an object type defined by a set of one or more attributes, each of the set of one or more attributes having associated therewith a corresponding set of one or more parameters, wherein the numerical value is determined using the set of text and a value of each of the set of one or more parameters for each of the set of one or more attributes. One of the plurality of objects that is most likely to be the subject of the set of text is identified based upon the numerical value that has been determined for each of the plurality of objects. | 04-28-2011 |
