| Patent application number | Description | Published |
|---|
| 20090265227 | Methods for Advertisement Display Policy Exploration - An exploratory ordering of advertisements is generated using an exploration policy that is a modified version of an existing policy. The exploration policy is defined to swap a pair of adjacent advertisements in an ordering of advertisements generated by the existing policy so to generate the exploratory ordering of advertisements. A top number of the exploratory ordering of advertisements are displayed. The top number corresponds to a number of available advertisement display spaces. Click data associated with display of the exploratory ordering of advertisements is collected. A revenue generation capability of a new policy is evaluated based on the collected click data. | 10-22-2009 |
| 20090287618 | DISTRIBUTED PERSONAL SPAM FILTERING - Embodiments are directed towards using a community of weighted results from local and global message classifiers to determine whether a message is spam. Each local classifier may receive a message that is to be evaluated to determine whether it is spam. A local classifier receives the message and performs a classification of the message. The local classifier may receive predictions of whether the message is spam from at least one global classifier. The local and global predictions are combined using, in one embodiment, a regression analysis to generate a single local message classification. Combining the local and global predictions is directed towards enabling a community of predictions to be used to classify messages. The user may then re-classify this output, which in turn is used as feedback to modify weights to the local and received global predictions for a next message. | 11-19-2009 |
| 20100010891 | METHODS FOR ADVERTISEMENT SLATE SELECTION - A computer implemented method is disclosed for controlling display of advertisements. The method includes selecting a policy that generates a slate of advertisements to be displayed when the policy is applied to a context. The method also includes applying the selected policy to the context to generate the slate of advertisements to be displayed, and displaying the slate of advertisements. The method further includes identifying a user-selected advertisement in the slate of advertisements, and calculating a cost of the user-selected advertisement to be charged to an owner of the advertisement. The cost is calculated based on the selected policy, the context, and the slate of advertisements. | 01-14-2010 |
| 20100057546 | SYSTEM AND METHOD FOR ONLINE ADVERTISING USING USER SOCIAL INFORMATION - An improved system and method for online advertising using user social information is provided. An advertising demand engine may be provided for selecting advertisements using user social information and online behavior to serve to a user for display. A social network engine may be provided for constructing a plurality of networks of correlated users from social network information and online behavior. These networks may be updated with additional online behavior. An advertisement previously selected by a user or by other users belonging to a network constructed using social information and online behavior may be sent to users belonging to the same network in response to a request to serve an advertisement. In other embodiments, a ranked list of advertisements selected by users in multiple networks may be determined, and advertisements may then be sent to users from the ranked list of advertisements. | 03-04-2010 |
| 20100131496 | PREDICTIVE INDEXING FOR FAST SEARCH - A system comprises a machine readable storage medium having an index that, given a set of inputs, a set of outputs, a set of input categories, and a scoring rule, provides an ordered subset of the outputs for each input category. The outputs within each subset are ordered by predicted score with respect to an input from one of the input categories. At least one processor is capable of receiving an input corresponding to at least one of the set of input categories. The processor is configured for scoring a reduced set of outputs against the received input using the scoring rule. The reduced set of outputs includes a union of the subsets of outputs associated with each input category to which the received inputs correspond. The processor is configured for outputting a list including a subset of the reduced set of outputs having the highest scores. | 05-27-2010 |
| 20100268710 | PERSONALIZED WEB SEARCH RANKING - A system and method for personalized search ranking may use a user's feedback to immediately reorder search results for this particular user so as to improve click-through rate. Upon receiving a query including one or more words, a search engine may identify a list of search results and display the search results on a search result page. A machine-learning module may collect information about a user's browsing activities on the result page, update estimates of relevance of the search results, and reorder the search result list to personalize it for the user. | 10-21-2010 |
| 20110110231 | VOLUNTARY ADMISSION CONTROL FOR TRAFFIC YIELD MANAGEMENT - Embodiments are directed towards employing an admission controller (AC) network device to coordinate voluntary requests by traffic source devices (TSDs) to transmit traffic over a network. The TSDs submit voluntary requests to transmit network traffic during an allocated time frame to the AC. The AC monitors historical network traffic data and, based on various allocation policies, provides permission to at least some of the TSDs in the form of a nonexclusive lease of bandwidth with a rate cap for an allocated time frame. The TSDs receiving the lease voluntarily agree to transmit traffic not exceeding the rate cap for the time frame of the lease. TSDs that receive a zero rate cap voluntarily agree not to transmit. However, urgent network traffic bypasses the AC. The allocation policies used to determine the rate cap and number of permitted senders include a reactive approach, a predictive approach, and a predictive-reactive approach. | 05-12-2011 |
| 20120016642 | CONTEXTUAL-BANDIT APPROACH TO PERSONALIZED NEWS ARTICLE RECOMMENDATION - Methods and apparatus for performing computer-implemented personalized recommendations are disclosed. User information pertaining to a plurality of features of a plurality of users may be obtained. In addition, item information pertaining to a plurality of features of the plurality of items may be obtained. A plurality of sets of coefficients of a linear model may be obtained based at least in part on the user information and/or the item information such that each of the plurality of sets of coefficients corresponds to a different one of a plurality of items, where each of the plurality of sets of coefficients includes a plurality of coefficients, each of the plurality of coefficients corresponding to one of the plurality of features. In addition, at least one of the plurality of coefficients may be shared among the plurality of sets of coefficients for the plurality of items. Each of a plurality of scores for a user may be calculated using the linear model based at least in part upon a corresponding one of the plurality of sets of coefficients associated with a corresponding one of the plurality of items, where each of the plurality of scores indicates a level of interest in a corresponding one of a plurality of items. A plurality of confidence intervals may be ascertained, each of the plurality of confidence intervals indicating a range representing a level of confidence in a corresponding one of the plurality of scores associated with a corresponding one of the plurality of items. One of the plurality of items for which a sum of a corresponding one of the plurality of scores and a corresponding one of the plurality of confidence intervals is highest may be recommended. | 01-19-2012 |
