Machanavajjhala
Ashwin Machanavajjhala, Millbrae, CA US
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20110264651 | LARGE SCALE ENTITY-SPECIFIC RESOURCE CLASSIFICATION - A system and method is described for large scale entity-specific classification of each entity-specific set of candidates in a collection of candidates for each specific entity in a collection of entities. The collection of entities may comprise a specific category or domain of entities (e.g. schools, restaurants, manufacturers, products, events, people). Candidates may comprise webpages or other resources with resource identifiers. Entity specific sets of candidates may be found by leveraging search engine query results and user interaction therewith for queries based on entity-specific attributes. The relationship(s) or class(es) for which candidate resources are being classified relative to a specific entity may comprise an authoritative, official home page (OHP), or other class (e.g. fan page, review, aggregator) relative to a specific entity. A feature generator generates entity-specific features for candidates. In accordance with its features, one or more classifiers rank each candidate for a specific class for a specific entity. | 10-27-2011 |
Ashwin Machanavajjhala, Baltimore, MD US
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20130159274 | User Behavior-Driven Background Cache Refreshing - Methods and system for providing social feeds from a plurality of third party sites to a user at a host site includes retrieving one or more access logs capturing online behavior of the user. The access logs are analyzed to determine the user's interactive behavioral pattern related to social feeds from each of the plurality of third party sites. A refresh schedule for the user is computed to refresh cache entries of social feeds at the host site based on the analysis of the user's online behavior at the social feeds. Cache entries of social feeds for the user are refreshed at the host site from the one or more of the plurality of third party sites at an allotted time specified by the refresh schedule. | 06-20-2013 |
Ashwin Kumar Machanavajjhala, Ithaca, NY US
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20090157589 | SYSTEM FOR OPINION RECONCILIATION - A system is disclosed for reconciling opinions generated by agents with respect to one or more predicates. The disclosed system may use observed variables and a probabilistic model including latent parameters to estimate a truth score associated with each of the predicates. The truth score, as well as one or more of the latent parameters of the probabilistic model, may be estimated based on the observed variables. The truth score generated by the disclosed system may enable publishers to reliably represent the truth of a predicate to interested users. | 06-18-2009 |
20100036865 | Method For Generating Score-Optimal R-Trees - A method of constructing a score-optimal R-tree to support top-k stabbing queries over a set of scored intervals generates a constraint graph from the set, and determines over each node in the constraint graph that has no other nodes pointing to it the node with the smallest left endpoint; for each of these nodes, the associated interval is added to the tree and the node is removed from the constraint graph. | 02-11-2010 |
Ashwin Kumar V. Machanavajjhala, San Ithaca, NY US
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20090112846 | SYSTEM AND/OR METHOD FOR PROCESSING EVENTS - The subject matter disclosed herein relates to processing information regarding events. In one particular example, a stabbing query may be formulated in response to an event. One or more sets are associated with and/or mapped to nodes of a tree. | 04-30-2009 |
Ashwin Kumar V. Machanavajjhala, Millbrae, CA US
Patent application number | Description | Published |
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20110153542 | OPINION AGGREGATION SYSTEM - A system is disclosed for obtaining and aggregating opinions generated by multiple sources with respect to one or more objects. The disclosed system uses observed variables associated with an opinion and a probabilistic model to estimate latent properties of that opinion. With those latent properties, the disclosed system may enable publishers to reliably and comprehensively present object information to interested users. | 06-23-2011 |