Patent application number | Description | Published |
20090198671 | SYSTEM AND METHOD FOR GENERATING SUBPHRASE QUERIES - A system for generating subphrase queries. The system includes a sequence label modeling engine and a regression modeling engine. The sequence label modeling engine generates a plurality of subphrase queries by indexing through each token in a search phrase and labeling each token based on an association to other tokens in the search phrase. The regression modeling engine scores each subphrase query at least partially on the association according to a scoring model. The regression modeling engine identifies the subphrase query with the highest score which may then be used for identifying a sponsored search list or a web search item. | 08-06-2009 |
20100070498 | OPTIMIZATION FRAMEWORK FOR TUNING RANKING ENGINE - Disclosed are apparatus and methods for facilitating the ranking of web objects. The method includes automatically adjusting a plurality of weight values for a plurality of parameters for inputting into a ranking engine that is adapted to rank a plurality of web objects based on such weight values and their corresponding parameters. The adjusted weight values are provided to the ranking engine so as to generate a ranked set of web objects based on such adjusted weight values and their corresponding parameters, as well as a particular query. A relevance metric (e.g., that quantifies or qualifies how relevant the generated ranked set of web objects are for the particular query) is determined. The method includes automatically repeating the operations of adjusting the weight values, providing the adjusted weight values to the ranking engine, and determining a relevance metric until the relevance metric reaches an optimized level, which corresponds to an optimized set of weight values. The repeated operations utilize one or more sets of weight values including at least one set that results in a worst relevance metric value, as compared to a previous set of weight values, according to a certain probability in order to escape local optimal solution to reach the global optimal solution. | 03-18-2010 |
20100114689 | SYSTEM FOR DISPLAY ADVERTISING OPTIMIZATION USING CLICK OR CONVERSION PERFORMANCE - An advertisement impression distribution system includes a data processing system operable to generate an allocation plan for serving advertisement impressions. The allocation plan allocates a first portion of advertisement impressions to satisfy guaranteed demand and a second portion of advertisement impressions to satisfy non-guaranteed demand. The data processing system includes an optimizer, the optimizer to establish a relationship between the first portion of advertisement impressions and the second portion of advertisement impressions. The relationship defines a range of possible proportions of allocation of the first portion of advertisement impressions and the second portion of advertisement impressions. The optimizer generates a solution in accordance with maximizing guaranteed demand fairness, non-guaranteed demand revenue and click or conversion value, where the solution identifies a determined proportion of the first portion of advertisement impressions to serve and a determined proportion of the second portion of advertisement impressions to serve. The data processing system outputs the allocation plan including the solution to control serving of the advertisement impressions in the determined proportions. | 05-06-2010 |
20100250523 | SYSTEM AND METHOD FOR LEARNING A RANKING MODEL THAT OPTIMIZES A RANKING EVALUATION METRIC FOR RANKING SEARCH RESULTS OF A SEARCH QUERY - An improved system and method for learning a ranking model that optimizes a ranking evaluation metric for ranking search results of a search query is provided. An optimized nDCG ranking model that optimizes an approximation of an average nDCG ranking evaluation metric may be generated from training data through an iterative boosting method for learning to more accurately rank a list of search results for a query. A combination of weak ranking classifiers may be iteratively learned that optimize an approximation of an average nDCG ranking evaluation metric for the training data by training a weak ranking classifier at each iteration for each document in the training data with a computed weight and assigned class label, and then updating the optimized nDCG ranking model by adding the weak ranking classifier with a combination weight to the optimized nDCG ranking model. | 09-30-2010 |
20100318513 | USER INTERFACE FOR NAVIGATING A KEYWORD SPACE - The present invention relates to systems, methods, and user interfaces for browsing a collection of content items saved by a user or by one or more buddies associated with a given user. The method of the present invention comprises saving one or more content items and one or more associated keywords as specified by a user. An interface is generated that displays the one or more saved content items and the one or more associated keywords, as well as the one or more buddies associated with a given user. A user indication of the selection of a given keyword or the selection of a given buddy by the user is received. The one or more displayed content items are filtered according to the selected keyword, buddy, or combination of selected keyword and buddy. | 12-16-2010 |
20110196739 | SYSTEMS AND METHODS FOR EFFICIENTLY RANKING ADVERTISEMENTS BASED ON RELEVANCY AND CLICK FEEDBACK - The present invention provides a method and system for ranking and selecting advertisements based on relevancy, click feedback and click over expected click (COEC) data. Advertisements may be described as contextual, page-embedded advertisements appearing on publisher websites. The method and system includes storing page-advertisement relevancy features in a vector space model and historical impression and click features in a click feedback model and analyzing data in the vector space model and click feedback model. The method and system further includes storing empirical click-through data in a serving log and analyzing data therein. The method and system then generates a regression model based on the analyzed data, which is stored in a regression storage module. The method and system receives requests for advertisement content from client devices, selects a plurality of candidate advertisements based on the generated regression model and provides a plurality of advertisements to a client device. | 08-11-2011 |
20120041961 | USER INTERFACE FOR NAVIGATING A KEYWORD SPACE - The present invention relates to systems, methods, and user interfaces for browsing a collection of content items saved by a user or by one or more buddies associated with a given user. The method of the present invention comprises saving one or more content items and one or more associated keywords as specified by a user. An interface is generated that displays the one or more saved content items and the one or more associated keywords, as well as the one or more buddies associated with a given user. A user indication of the selection of a given keyword or the selection of a given buddy by the user is received. The one or more displayed content items are filtered according to the selected keyword, buddy, or combination of selected keyword and buddy. | 02-16-2012 |
20120084142 | BID LANDSCAPE FORECASTING IN ONLINE ADVERTISING - Techniques are provided for advertiser bid forecasting in online advertising, including display advertising. Methods are provided in which key targeting-related user segments are determined from bidding statistics. A feature set is extracted from an impression opportunity, based at least in part on the bidding statistics. A gradient boosting descent tree technique is utilized in determining an initial bid forecasting result. A linear regression-based model is used in post-tuning to arrive at a post-tuned result. For short-term forecasting, this may be the final result. For long-term forecasting, a hybrid approach may be utilized with further processing including utilization of a publisher-specific model. | 04-05-2012 |
20120191541 | INVENTORY ALLOCATION FOR ADVERTISING WITH CHANGEABLE SUPPLY LANDSCAPE - An advertisement impression distribution system is programmed to generate an allocation plan for serving a number of advertisement impressions changeable as a result of one or more events, the allocation plan to allocate a first portion of advertisement impressions to satisfy guaranteed demand and a second portion of advertisement impressions to satisfy non-guaranteed demand. The system includes an optimizer programmed to establish a relationship between the first portion of advertisement impressions and the second portion of advertisement impressions, the relationship defining a range of possible proportions of allocation of the first portion of advertisement impressions and the second portion of advertisement impressions; and to impose at least one objective on the relationship including moderating an increase in the number of advertisement impressions available for allocation to the first and second portions, to minimize a cost associated with reducing a quality of the advertisement impressions as their volume increases. The system outputs the allocation plan to an ad serving module to control serving of the advertisement impressions according to the range of possible proportions of allocation between the first and the second portions. | 07-26-2012 |
20130085845 | FACILITATING DEAL COMPARISON AND ADVERTISING IN ASSOCIATION WITH EMAILS - Techniques are provided which improve deal and advertisement targeting of users, and which may include facilitating user comparison of deals. Methods and systems may detect if an email contains deal information related to one or more deals. If an email contains deal information, the deal information may be extracted. When the email is opened by the user, a link may be displayed on top of (e.g., overlaid on) the email. The link may be configured such that clicking on the link transmits a search query comprising the extracted deal information to a deal service. The deal service may retrieve one or more additional deals which may be similar or related to the one or more deals received in the email. The additional deals may be selected by the deal service based at least in part on the extracted deal information. | 04-04-2013 |
20130085852 | DEAL AND AD TARGETING IN ASSOCIATION WITH EMAILS - Techniques are provided which improve deal and advertisement targeting of users. Methods and systems may detect if an email contains deal information related to one or more deals. If an email contains deal information, the deal information may be extracted. If the user clicks on a link in the email, one or more additional deals which may be similar or related to the one or more deals received in the email may be selected based at least in part on the extracted deal information. The additional deals and/or advertisements related to the additional deals may be targeted to the user via email or via the user's browser application. | 04-04-2013 |
20130226918 | TRUST PROPAGATION THROUGH BOTH EXPLICIT AND IMPLICIT SOCIAL NETWORKS - The present invention is directed towards systems and methods for trust propagation. The method according to one embodiment comprises calculating a first feature vector for a first user, calculating a second feature for a second user and comparing the first feature vector with the second feature vector to calculate a similarity value. A determination is made as to whether the similarity value falls within a threshold. If the similarity value falls within the threshold, a relationship is recorded between the first user and the second user in a first user profile and a second user profile. | 08-29-2013 |
20140289232 | Search system and methods with integration of user annotations from a trust network - Computer systems and methods incorporate user annotations (metadata) regarding various pages or sites, including annotations by a querying user and by members of a trust network defined for the querying user into search and browsing of a corpus such as the World Wide Web. A trust network is defined for each user, and annotations by any member of a first user's trust network are made visible to the first user during search and/or browsing of the corpus. Users can also limit searches to content annotated by members of their trust networks or by members of a community selected by the user. | 09-25-2014 |