Yahoo! Inc.

Excalibur Ip, LLC

Sudarshan Lamkhede

Yi Chang

Belle L Tseng

Bo Long

Shenhong Zhu

Srinivas Vadrevu

Anlei Dong

Hongbo Deng

Jiuhe Gan

Peter Mika

Youssef Billawala

Vinod Balakrishnan

Ya Zhang

Methods, systems and programming for providing query suggestions including entities. In one example, a prefix of a query is first received. A plurality of query suggestions are then identified based on the prefix of the query. The plurality of query suggestions include at least one entity. Scores of each of the plurality of query suggestions are computed using a first model. The first model includes an adjustable parameter used for computing the score of the at least one entity. The plurality of question suggestions are ranked based, at least in part, on the scores.

Method and system for providing query suggestions including entities

Methods, systems and programming for entity recognition in a query. In one example, an index that associates an alias with one or more entities is obtained. Each of the one or more entities is associated with one or more features. A query associated with one or more features is received from a user. The alias is then identified in the query. At least one of the one or more entities is determined based, at least in part, on the features associated with each of the one or more entities and the features associated with the query.

Method and system for entity recognition in a query

An information retrieval system and computer-based method provide constructing a title for a search result summary of a document through title synthesis, wherein the title is suitable for use in assessing the relevance of the summarized document to a query. Meaningful keywords or key phrases (title components) about the document are Obtained. The title components are classified into pre-established title component classes. When a query is input to which the document is relevant, a title for the document is constructed by arranging title components selected from title component classes to maximize a title utility function. The title utility function may be a query-dependent grade. In addition to the query, the title utility function may also account for constraints under which the title is to be presented to a user.

Automatically constructing titles

According to an example embodiment, a method comprises executing instructions by a special purpose computing apparatus to, for labeled source domain data having a plurality of original labels, generate a plurality of first predicted labels for the labeled source domain data using a target function, the target function determined by using a plurality of labels from labeled target domain data. The method further comprises executing instructions by the special purpose computing apparatus to apply a label relation function to the first predicted labels for the source domain data and the original labels for the source domain data to determine a plurality of weighting factors for the labeled source domain data. The method further comprises executing instructions by the special purpose computing apparatus to generate a new target function using the labeled target domain data, the labeled source domain data, and the weighting factors for the labeled source domain data, and evaluate a performance of the new target function to determine if there is a convergence.

System and method for cross domain learning for data augmentation

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Santa Clara, CA, United States of America

Sudarshan Lamkhede