Yahoo! Inc.

Salesforce Com, Inc.

Excalibur Ip, LLC

R2 Solutions, LLC

Bento Labs Inc.

Kunal Punera

Deepayan Chakrabarti

Shanmugasundaram Ravikumar

Suju Rajan

Tamas Sarlos

Theodoros Lappas

Anirban Dasgupta

Adam Evans

Steve Loughlin

Andrei Z Broder

Scott J Gaffney

Belle L Tseng

Parth Shah

Srinivas Vadrevu

Nikhil Vijay Chandhok

Xuanhui Wang

Gary Lerhaupt

Jason Li

Maxim Gurevich

Patricio Echague

Choon Hui Teo

Nelson Lance Osacky

Jeffrey Leon

Hung-Kuo (James) Chu

Scott Bessler

Andrea Hawksley

Kyle David Wilkinson

Descriptive data relating to at least a subset of a plurality of entities on a website is retrieved over a network. Endorsement data relating to the plurality of entities is retrieved from the website. A first set of probabilities is determined reflecting a probability that endorsements can be attributed to specific aspects. A second set of probabilities is determined reflecting a probability that terms can be attributed to aspects. Using the first set of probabilities and the second set of probabilities, a subset of the terms that are most probably associated with each entity are selected. Tags are then generated for each entity using the selected terms.

Computerized system and method for determining non-redundant tags from a user's network activity

A method and apparatus for the automatic suggestion generation in a relationship management system is described. The method may include obtaining an electronic communication associated with one or more users of a relationship management system, where the communication is part of a series of communications in a process managed by the relationship management system. Furthermore, the method may include analyzing content of the electronic communication to determine a suggested future action within the process managed by the relationship management system. The method may also include generating a suggestion by the relationship management system to notify at least one user of the suggested future action, and storing the generated suggestion within a database coupled with the relationship management system.

Systems and methods for automatic suggestions in a relationship management system

A method and apparatus for the automatic creation of a relationship management system is described. The method may include receiving a request from a user to create a relationship management system, and receiving specification of one or more electronic communication systems and user access credentials that provide access to each of the corresponding accounts. Furthermore, the method may include obtaining past electronic communications using the received user access credentials and analyzing the past electronic communications to extract contact data. The method may also include creating the relationship management system for the user and adding the contact data as contacts associated with the user in the created relationship management system.

Systems and methods for automatic generation of a relationship management system

A method and apparatus for performing anticipatory push search for a homescreen browser of a mobile device is described. The method may include collecting profile data indicative of behavior of a user with respect to usage of a mobile device and constructing a user profile for an anticipated usage of the mobile device by the user. Furthermore, the method may include publishing a content search request based on the anticipated usage of the mobile device by the user, and receiving at least one content response from a content provider. The method may also include providing content from the content response to the mobile device based on the anticipated usage of the mobile device by the user, the content for populating an anticipatory homescreen browser displayed by the mobile device.

Systems and methods for anticipatory push search for a homescreen browser

System and method for mining tags using social endorsement networks

A method and apparatus is described for assigning functional labels to segments of web pages in an application-independent way. In the approach described herein, one of a generic set functional labels are automatically assigned to each segment of a web page, where the generic functional labels may be topic-independent and application-independent. Applications with different needs can determine which segments of the web page to process based on which functional labels correspond to the types of information needed by each application. Thus, the work of classifying the function of each segment of a web page is separated from the work of selecting which segments satisfy the need of a particular application. The work of classification can be performed in an application-independent way, relieving the burden from every application developer from having to create their own classifiers.

Annotating HTML segments with functional labels

An optimization-based framework is utilized to extract broad query aspects from query reformulations performed by users in historical user session logs. Objective functions are optimized to yield query aspects. At run-time, the best broad but unspecified query aspects relevant to any user query are presented along with the results of the run time query.

Mining broad hidden query aspects from user search sessions

A method and apparatus for receiving training data that comprise a plurality of event-and-time-specific texts that are contextually related to a plurality of events; iteratively processing the training data to generate a modified network model that defines a plurality of states; receiving additional data that comprise a plurality of additional event-and-time-specific texts that are contextually related to a particular event; processing the additional data by applying the modified network model to the additional data to identify, within the plurality of additional event-and-time specific texts, a particular set of texts that belong to a particular state of the plurality of states; identifying, within the particular set of texts, one or more texts that are most representative of all texts in the particular set of texts that belong to the particular state; wherein the method is performed by one or more special-purpose computing devices.

Method for summarizing event-related texts to answer search queries

A method of generating a time managed challenge-response test is presented. The method identifies a geometric shape having a volume and generates an entry object of the time managed challenge-response test. The entry object is overlaid onto the geometric shape, such that the entry object is distributed over a surface of the geometric shape, and a portion of the entry object is hidden at any point in time. The geometric shape is rotated, which reveals the portion of the entry object that is hidden. A display region on a display is identified for rendering the geometric shape and the geometric shape is presented in the display region of the display.

Time managed challenge-response test

Disclosed are methods and apparatus for clustering news stories, which are to be presented over a computer network. In general, an incremental clustering system is configured to update a current set of news clusters with newly arrived news articles without having to recompute the clusters for the entire corpus, as well as form new clusters for recently generated news topics. In one embodiment, a plurality of news articles are initially obtained via the computer network, and the news articles are clustered into a plurality of initial clusters. For only news articles, including any unclustered news articles, that are less than a predetermined age limit, it is determined in an incremental clustering process whether to form one or more new clusters or assign to the initial clusters. Indications of the initial clusters and the one or more new clusters, if any, are then stored so as to be accessible for sending a portion of the news articles to users in a clustered format based on the initial clusters and the one or more new clusters, if any.

System for incrementally clustering news stories

A system and method for implementing a multi-step challenge and response test includes steps or acts of: using an input/output subsystem for presenting a series of challenges to a user that require said user to correctly solve each challenge before a next challenge is revealed to the user; receiving the user's response to each challenge; and submitting a last response in the series of challenges to a server for validation. The method further includes: using a processor device configured to perform for each challenge in the series of challenges: internally validating the response by comparing the user's response to a correct response; and using the user's response, decrypting the next challenge to reveal the next challenge; wherein the next challenge remains obfuscated until a previous challenge is correctly solved.

Multi-step captcha with serial time-consuming decryption of puzzles

A method and apparatus are provided for utilizing social network information to show reviews written by others. In one example, the method includes uploading at least one review written by an entity other than a particular user; filtering the at least one review according to criteria specified by the particular user; and integrating into one central location reviews written by others, wherein the reviews include the at least one review.

Method and apparatus for utilizing social network information for showing reviews

Methods, computer programs, and systems for generating a link title for a URL (Uniform Resource Locator) within a context webpage to be shown as a web result are provided. The method evaluates generation parameters for a plurality of sources for picking words from the link title. Further, the method generates candidates for the link title, and a likelihood is computed for each candidate. When computing the likelihood, the generation parameters, the context webpage and the words are considered. In addition, the method selects a candidate with the highest likelihood from all the computed likelihoods, and presents the URL with the selected candidate as the title.

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San Francisco, CA, United States of America

Kunal Punera