Patent application number | Description | Published |
20080295006 | DYNAMIC LAYOUT FOR A SEARCH ENGINE RESULTS PAGE BASED OF IMPLICIT USER FEEDBACK - The present invention is directed towards systems and methods for providing dynamic search results based upon historical data through the use of one or more widgets. The method of the present invention comprises receiving a request for content from a client and generating one or more widgets for providing search result content. A display profile is applied to the one or more widgets and the one or more widgets are combined with static search results to form a search result page that is provided to a requesting client. | 11-27-2008 |
20090157559 | SYSTEM AND METHOD FOR INTERNET MARKETING BY ENDORSEMENTS - A method of facilitating the endorsement of products through Internet advertisements accepts a bid for an endorsement, enables communication, associated with the bid, between an advertiser and a potential endorser, and serves an endorsement associated with the bid. In one implementation, the endorsement is displayed together with a symbol verifying the endorser. | 06-18-2009 |
20090276729 | ADAPTIVE USER FEEDBACK WINDOW - The subject matter disclosed herein relates to maintaining a history of user interaction data within a sliding window, where the sliding window may be sized based at least in part on a quantification of such user interaction. | 11-05-2009 |
20110125572 | OPTIMIZATION OF SPONSORED SEARCH SYSTEMS WITH REAL-TIME USER FEEDBACK - Search and advertising systems may be optimized through the use of user feedback. Selected parameters such as ranking, filtering, placement, and pricing may be optimized to achieve certain objectives. The optimization may include real-time user monitoring of multiple configurations with various parameters. In one embodiment, a subset of user queries may be assigned to a particular configuration for monitoring and measuring the real-time performance of that configuration. The performance for multiple configurations may be used to identify optimal settings. | 05-26-2011 |
20110246286 | CLICK PROBABILITY WITH MISSING FEATURES IN SPONSORED SEARCH - Sponsored search advertising utilizes a click probability as one factor in selecting and ranking advertisements that are displayed with search results. The probability of click may also be referred to as a predicted click-through rate (“CTR”) that may be multiplied by an advertiser's bid for a particular advertisement to rank the display of advertisements. An accurate prediction of the click probability improves the potential revenue that is generated by advertisements in a pay per click system. Other advertising systems may benefit from an accurate and reliable estimate for an advertisement's probability of click in different environments and scenarios. | 10-06-2011 |
20110289079 | DYNAMIC LAYOUT FOR A SEARCH ENGINE RESULTS PAGE BASED ON IMPLICIT USER FEEDBACK - The present invention is directed towards systems and methods for providing dynamic search results based upon historical data through the use of one or more widgets. The method of the present invention comprises receiving a request for content from a client and generating one or more widgets for providing search result content. A display profile is applied to the one or more widgets and the one or more widgets are combined with static search results to form a search result page that is provided to a requesting client. | 11-24-2011 |
20120022952 | Using Linear and Log-Linear Model Combinations for Estimating Probabilities of Events - A method for combining multiple probability of click models in an online advertising system into a combined predictive model, the method commencing by receiving a feature set slice (e.g. corresponding to demographics or taxonomies or clusters), and using the sliced data for training multiple slice-wise predictive models. The trained slice-wise predictive models are combined by overlaying a weighted distribution model over the trained slice-wise predictive models. The combined predictive model then is used in predicting the probability of a click given a query-advertisement pair in online advertising. The method can flexibly receive slice specifications, and can overlay any one or more of a variety of distribution models, such as a linear combination or a log-linear combination. Using an appropriate weighted distribution model, the combined predictive model reliably yields predictive estimates of occurrence of click events that are at least as good as the best predictive model in the slice-wise predictive model set. | 01-26-2012 |
20120136722 | Using Clicked Slate Driven Click-Through Rate Estimates in Sponsored Search - A computer-implemented method and system for selecting a subject advertisement in a sponsored search system based on a user's commercial intent (pertaining to the subject advertisement), using techniques for determining intent-driven clicks from a historical database. The method includes steps for aggregating a training model dataset wherein the training model dataset contains a selected history of clicks. Then, selecting from the training model dataset, a clicked slate (further selection of clicks), the clicked slate comprising a set of clicked ads, and calculating an intent-driven click feedback value for the subject advertisement. The method includes techniques for selecting a clicked slate using features corresponding to clicks received within a particular time period (the time period determined statically or dynamically). A system for implementing the method includes aggregating data from a historical database using selectors such as a position selector, a click feature selector, an impression-advertiser-campaign-creative selector, and a commercial intent selector. | 05-31-2012 |