Yahoo! Inc.

Yahoo Assets LLC

Verizon Media Inc.

Rohan Monga

Sudharsan Vasudevan

Hemanth Sambrani

Priyank Garg

Sanjeev Gupta

N S Sekar

Managing electronic addresses based on communication patterns. A method includes tracking metadata of a plurality of electronic communications of a user. One or more lists of electronic addresses of recipients are generated for the user based on the metadata. Electronic addresses of potential recipients are identified from the one or more lists in response to an input indicative of selection of an electronic address of a recipient. The identified electronic addresses are recommended to the user. An input indicative of one or more electronic addresses selected by the user from the identified electronic addresses is received. Further, an electronic message is sent to the selected electronic addresses.

Managing electronic addresses based on communication patterns

A system and method for an enhanced find-in-page query function in a web browser. A find-in-page query is received for at least one webpage displayed on a computing device, wherein the query comprises a search string. Metadata relating to data objects displayed on the webpage is collected from the HTML code comprising the webpage, from the source of the of the plurality of objects, and from at least one search engine. At least one of the plurality of data objects matching the find-in-page query is identified wherein the search string is matched to metadata, wherein metadata relating to the matching data objects comprises the search string. The display of the matching data objects on the webpage is then altered, using the computing device, whereby the user is able to identify the data objects which match the find-in-page query.

Enhanced find-in-page functions in a web browser

Disclosed is a method and system for retrieving data; extracting information from the data; learning to disambiguate the extracted information such that a particular sense of each phrase within the extracted information is determined; generating a disambiguation classifier from the learning to disambiguate step, the disambiguation classifier configured to determine a sense of a phrase within a document; learning to select a portion of the information as being relevant to a theme of the data; generating a selection classifier from the learning to select step, the selection classifier configured to select a topic in a document that is relevant to a theme of the document; and using the disambiguation classifier and the selection classifier by an indexing computer to determine a set of topics from a web document retrieved by the indexing computer.

Large scale concept discovery for webpage augmentation using search engine indexers

A method and apparatus for activity-based users' interests modeling for determining relevance of the content distributed to the users is provided. Modeling of the user's interests starts by collecting information about the actions that the user performed and about the contents that were associated with the actions. That information may be used to determine how much interest the user has had in the individual subjects up to date, and to determine which subjects became more or less important to the user over time. Further processing of the information about the interests of each of the individual users in a group of users may produce characteristics indicating the interests of the group as a whole. Additional processing may generate the information reflecting relative importance of the interests of an individual user in the group to the interests of other users in the same group.

Activity based users' interests modeling for determining content relevance

Techniques are provided for creating and updating a entity hierarchy (taxonomy) based on information captured about user interaction with a system. Techniques are also provided for using the taxonomy to determine the nature of entities represented by terms submitted to a search engine. Search logs analyzed for related sets of entities, and used to improve the taxonomy for storing information. Once the taxonomy is created, information across data sources are fetched and aggregated based on the taxonomy. When the system is queried, the query is modified to a predefined template, and the best fit result is promptly returned. A feedback mechanism is also provided to enhance taxonomy and entity data based on search volumes. This system enables search engines to provide accurate answers when entities, their attributes and relationships are involved.

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Punjab, India

Rohan Monga