Yahoo! Inc.

AT&T Intellectual Property I, LP

At+t Corp.

Match Group, LLC

Match.com, L.l.c.

Sihem Amer-Yahia

Cong Yu

Divesh Srivastava

Ronny Lempel

Nadav Golbandi

Fernando David Diaz

Donald Metzler

Moran Feldman

Nikolaos Koudas

Cameron A Marlow

Ronald J Brachman

Maria F Fernandez

Munmun De Choudhury

Yu Xu

Amélie Marian-Guerrier

Frederick K Schmidt

Bo Pang

Dan Suciu

Evgeniy Gabrilovich

Sergei Vassilvitskii

David Christopher Parkes

Ramana Yerneni

David Myer Pennock

Julia Stoyanovich

Nikolas Koudas

David Toman

Munmum De Choudhury

Sebastien Lahaie

Laks Lakshmanan

Alban Galland

Amelie Marian

Disclosed are methods and apparatus for automatically determining the relevance of matches between entities. A set of one or more indicators of relevance for each of a plurality of matches may be detected, where each of the plurality of matches exists between a first entity and a different one of a plurality of entities. Each set of one or more indicators of relevance indicates a degree of two-way interest for a corresponding one of the plurality of matches, the degree of two-way interest indicating both a degree of interest of the first entity in the corresponding one of the plurality of entities and a degree of interest of the corresponding one of the plurality of entities in the first entity. A probability of relevance of each of the plurality of matches may be determined based at least in part upon a corresponding set of one or more indicators of relevance. Each of the plurality of matches may be ranked based at least in part on the corresponding probability of relevance. A ranking function may be trained based upon the probability of relevance of each of the plurality of matches. The ranking function may subsequently be applied to identify and rank matches (e.g., in the absence of indicators of relevance).

System for determining and optimizing for relevance in match-making systems

Methods and systems are provided for providing recommendations to users of a computer-based network of items of potential interest to the users. Items and people of potential interest to users may be determined using obtained word-based social behavior information, semantically-sensitive vocabulary taxonomies, and determined implied topic-specific social networks. The user may be presented with a graphical user interface including the recommendation, an explanation of the rationale relating to the recommendation, and an opportunity for the user to provide feedback relating to the recommendation or the rationale. The feedback may be used to improve future recommendations.

Recommendation system using social behavior analysis and vocabulary taxonomies

One embodiment accesses two or more photos taken by one or more travelers at one or more destinations and one or more points-of-interest located within the destinations; constructs one or more photo streams for each unique traveler-destination combination, wherein each one of the photo streams comprises two or more of the photos taken by the corresponding traveler at the corresponding destination; maps each one of the photos to one of the points-of-interest; constructs one or more timed paths for each unique traveler-destination combination based on the photo streams and the mapping between the photos and the points-of-interest, wherein each one of the timed paths comprises one or more of the points-of-interest located within the corresponding destination and visited by the corresponding travel; and constructs an itinerary based on a start point-of-interest, an end point-of-interest, a time constraint, and the timed paths.

Constructing travel itineraries from tagged geo-temporal photographs

An embodiment of the present invention automatically detects when a user is in a state of vacillation based on user on-line behavior, records relevant parameters regarding the vacillation event, and then responds accordingly. This response may include providing relevant and/or targeted information that can be used by the user to help remove the indecision. The response may also or alternatively include providing third-party businesses, such as retailers, marketers, and advertisers, with information about vacillation events and associated behaviors for a single user or groups of users so that such businesses can identify potential markets/customers or directly engage similar users to facilitate the decision-making process.

User vacillation detection and response

A method of adaptively evaluating a top-k query involves () forming a servers having respective server queues storing candidate answers, processing () the candidate answers, and () providing a top-k set as a query evaluation. Processing includes () adaptively choosing a winning server to whose queue a current candidate answer should be sent; () sending the current candidate answer to the winning server's queue; () adaptively choosing a next candidate answer to process from the winning server's queue; () computing a join between the current candidate answer and next candidate answers at the winning server, so as to produce a new current candidate answer; and () updating the top-k set with the new current candidate answer only if a score of the new current candidate answer exceeds a score of a top-k answer in a top-k set. A method of calculating scores for candidate answers is also provided.

[object Object]

A method of searching a document having nested-structure document-specific markup (such as Extensible Markup Language (XML)) involvesreceiving a query that designates at least (A) a phrase to be matched in a phrase matching process, and (B) a selective designation of at least a tag or annotation that is to be ignored during the phrase matching process. The method further involvesderiving query-specific indices based on query-independent indices that were created specific to each document, andcarrying out the phrase matching process using the query-specific indices on the document having the nested-structure document-specific markup.

Phrase matching in documents having nested-structure arbitrary (document-specific) markup

A method and apparatus are provided for administering a bidding language for online advertising. In one example, the method includes providing an expressive bidding language that allows an advertiser to specify an ad campaign in a tree structure, receiving the ad campaign that is written in the expressive bidding language, translating the ad campaign into scripts, and using the scripts to access appropriate inventory from an ad inventory database.

Method and apparatus for administering a bidding language for online advertising

Methods and apparatus for making recommendations of content items to users of computer systems include compiling a database relating a list of items and corresponding explanations; receiving from a user, through a computer user interface, a request for a recommendation; extracting from the database a preliminary list of items related to the request; identifying distances between the extracted items based on the explanation corresponding to each item; and identifying a subset of the preliminary list to form a recommendation list having a limited number of recommendation results with a desired balance of both high relevancy and high diversity relative to each other.

Diversifying recommendation results through explanation

An improved method for information retrieval in web query and recommendation systems, where items that are likely unfamiliar to the users of the system, but potentially relevant, are recommended. In a recommendation system having ratings by a plurality of users for a plurality of items, items are assigned to one or more data regions based on item attributes or user activity. Source regions are identified for each of the data regions. For a given user, data regions with which both the user and the user's social network are unfamiliar are identified. Within a given data region, the relevance of items to the user within such regions is evaluated using ratings provided by other users who have entered ratings similar to the user in source regions for the data region. Items receiving the highest relevance score are recommended to the user.

System and method for finding unexpected, but relevant content in an information retrieval system

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New York, NY, United States of America

Sihem Amer-Yahia