Patent application number | Description | Published |
20090292688 | ORDERING RELEVANT CONTENT BY TIME FOR DETERMINING TOP PICKS - A computer-readable medium encoded with computer instructions for providing relevant content on a web page for a user is provided. According to embodiments of the invention, the instructions are for determining a relevance metric for at least two articles. Each article of the at least two articles is selected from content of the user. Each article is associated with a time. The instructions further include instructions for selecting a set of relevant articles based on the relevance metric and ordering the set of relevant articles according to the associated time of each article of the set. The instructions also include instructions for providing the ordered set of relevant articles to the user. | 11-26-2009 |
20100082594 | BUILDING A TOPIC BASED WEBPAGE BASED ON ALGORITHMIC AND COMMUNITY INTERACTIONS - Methods and system for generating a topic page for a search query on a search webpage includes receiving a search query at the search engine on a server from a search webpage on a client. The search engine examines the query and categorizes the query along one or more dimensions. A plurality of modules having dynamic content and associated with the one or more categories is identified and a glue page is generated using the identified modules. The glue page is integrated into a topic page. The topic page is returned to the client where it is rendered at the search webpage in response to the search query. | 04-01-2010 |
20100125585 | Conjoint Analysis with Bilinear Regression Models for Segmented Predictive Content Ranking - Information with respect to users, items, and interactions between the users and items is collected. Each user is associated with a set of user features. Each item is associated with a set of item features. An expected score function is defined for each user-item pair, which represents an expected score a user assigns an item. An objective represents the difference between the expected score and the actual score a user assigns an item. The expected score function and the objective function share at least one common variable. The objective function is minimized to find best fit for some of the at least one common variable. Subsequently, the expected score function is used to calculate expected scores for individual users or clusters of users with respect to a set of items that have not received actual scores from the users. The set of items are ranked based on their expected scores. | 05-20-2010 |
20100228712 | Algorithmically Generated Topic Pages with Interactive Advertisements - A method and system for generating a topic page for a search query on a search webpage includes receiving a query at the search webpage on a client. The query is transmitted from the search webpage on the client to a search engine on a server. A topic page generator available to the search engine analyzes the query to identify a plurality of dimensions. One or more content modules, including at least one interactive advertising module, that match one or more of the dimensions are selected from a plurality of sources based on a weight associated with each of the content modules. The weight defines the ranking of a content module. The content modules for the plurality of dimensions are glued together and presented on the topic page in the order of the corresponding weight of the content modules. The order of presentation identifies the relevancy of the content modules to the query. The presented topic page provides the most relevant content modules for the query, and for a user located in a specific geo location. | 09-09-2010 |
20100250556 | Determining User Preference of Items Based on User Ratings and User Features - A set of item-item affinities for a plurality of items is determined based on collaborative-filtering techniques. A set of an item's nearest neighbor items based on the set of item-item affinities is determined. A set of user feature-item affinities for the plurality of items and a set of user features is determined based on least squared regression. A set of a user feature's nearest neighbor items is determined based in part on the set of user feature-item affinities. Compatible affinity weights for nearest neighbor items of each item and each user feature are determined and stored. Based on user features of a particular user and items a particular user has consumed, a set of nearest neighbor items comprising nearest neighbor items for user features of the user and items the user has consumed are identified as a set of candidate items, and affinity scores of candidate items are determined. Based at least in part on the affinity scores, a candidate item from the set of candidate items is recommended to the user. | 09-30-2010 |
20110202821 | BIDDED MARKETPLACE FOR APPLICATIONS - Methods and systems for presenting application modules on a graphical display page are provided. In accordance with one embodiment, content to be displayed on a graphical display page is determined. Then, content features which describe the content that is to be displayed on the graphical display page, and user features which describe characteristics of users are determined. For each application in the plurality of application modules, the probability that specific users will select the application module when displayed on the graphical display page with the determined content is determined based on the content features and the user features. For each application module in the plurality of application modules, an overall score is determined based on the determined probability that the user will select the application module and a commercial value to be paid by a publisher of the application module when it is selected. The recommended application modules are determined to be those application modules in the plurality of application modules which have the highest overall score and which satisfy a set of constraints. Representations of the recommended application modules are displayed on the graphical display page. | 08-18-2011 |
20120084155 | PRESENTATION OF CONTENT BASED ON UTILITY - Methods and systems for presenting content such as articles based on utility are provided. In one embodiment, a plurality of articles are determined, each article in the plurality of articles including article content and a corresponding preview icon, the preview icon defining a link to the corresponding article content when presented. For each article in the plurality of articles, a user experience utility value is determined. And for each article in the plurality of articles, an economic utility value is also determined. A ranked order of the articles is determined based upon each article's user experience utility value and economic utility value. And a portion of the preview icons of the articles are presented on a graphical display page in a priority orientation based on the ranked order of the articles. | 04-05-2012 |
20130031470 | METHOD AND SYSTEM FOR PERSONALIZING WEB PAGE LAYOUT - Method and system for generating personalizing website layout. The method and system monitors a user's behaviors and assigns a user to a user group, which has an assigned personalized template. The templates are personalized in response to the user's behaviors and arranges content to be displayed to the user based on that behavior. | 01-31-2013 |
20130054593 | DETERMINING USER PREFERENCE OF ITEMS BASED ON USER RATINGS AND USER FEATURES - A set of item-item affinities for a plurality of items is determined based on collaborative-filtering techniques. A set of an item's nearest neighbor items based on the set of item-item affinities is determined. A set of user feature-item affinities for the plurality of items and a set of user features is determined based on least squared regression. A set of a user feature's nearest neighbor items is determined based in part on the set of user feature-item affinities. Compatible affinity weights for nearest neighbor items of each item and each user feature are determined. Based on user features of a user and items a user has consumed, a set of nearest neighbor items are identified as a set of candidate items, and affinity scores of candidate items are determined. Based on the affinity scores, a candidate item from the set of candidate items is recommended to the user. | 02-28-2013 |
20140075293 | WEB PAGE LAYOUT - Embodiments disclosed herein may relate to producing a layout for a web page. | 03-13-2014 |