Microsoft Technology Licensing, LLC

Esposito, Mario

Jian-Tao Sun

Zheng Chen

Xiaochuan Ni

Jian Hu

Gang Wang

Jian Wang

Shipeng Li

Zhimin Zhang

Xuedong D Huang

Ning Liu

Min Wang

Hua-Jun Zeng

Ying-Qing Xu

Shen Huang

Tao Mei

Ning Zhang

Dou Shen

Xuanhui Wang

Wei-Ying Ma

Ming Zhou

Jun Yan

Benyu Zhang

Peng Xu

Ye-Yi Wang

Weizhu Chen

Li Jiang

Lei Ji

Xiaolong Li

Huan Liu

Ke Tang

Mario Esposito

Jianmin Wu

Christoph Ponath

Qionghua Wang

Peng Bai

Jianwen Zhang

Qiang Yang

Ling Bao

Searching is assisted by recognizing a selection of text from a document as an indication that a user wishes to initiate a search based on the selected text. The user is provided with query suggestions based on the selected text and the query suggestions are ranked based on a context provided by the document. The user may select the text by using a mouse, drawing a circle around the text on a touch screen, or by other input techniques. The query suggestions may be based on query reformulation or query expansion techniques applied to the selected text. Context provided by the document is used by a language model and/or an artificial intelligence system to rank the query suggestions in predicted order of relevance based on the selected text and the context.

Context-based search query formation

Techniques for utilizing data mining technology to extract universal topics with multilingual representations from a multilingual database, and to organize existing or new documents in different languages by analyzing their respective topic distributions.

Mining multilingual topics

A computer-readable storage medium having stored thereon computer-executable instructions which, when executed by a computer, cause the computer to implement an opinion search engine. The instructions to implement an opinion search engine cause the computer to collect opinion data about one or more objects from the Internet, extract metadata about the opinion data from the opinion data, remove duplicate metadata from the metadata to generate a resulting metadata, categorize the resulting metadata for similar objects according to one or more taxonomies from one or more websites on the Internet and rank the similar objects based on the categorized metadata.

Opinion search engine

Techniques and technologies for expanding a gallery by seeding the gallery with seed query results. A template is identified which is associated with the subjects of the seed queries and content identifiers are identified which include the template. These content identifiers are used to expand the gallery to include more content identifiers than before the expansion of the gallery.

Query expansion through searching content identifiers

Embodiments of the present invention relate to systems, methods, and computer-storage media for a method of contextually analyzing terms within a search query. In one embodiment, a received search query is classified into a domain category. Additionally, information is assigned to a schema associated with the domain by analyzing the search query. Further, at least one search result that helps a user complete a task within the domain is provided based on the information in the schema.

Dialog-enhanced contextual search query analysis

An exemplary computer implemented graphics-based Web search system includes a search input control and a results presentation control where the search input control is configured to receive user input to establish a relationship between a query and one or more information tags associated with search results provided by a search engine in response to the query and wherein the results presentation control is configured to re-order the search results in response to the relationship. Such a system allows a user to define and refine search intent and enhance the user's search experience. Various other exemplary systems, methods, devices, etc. are also disclosed.

GUI based web search

Providing sentiment classification of out of domain data are disclosed herein. In some aspects, a source domain having a trained classifier is matched to a target domain having a target classifier. The trained classifier may include identifiers that may be used to predict the sentiment of opinion data for the source domain. The target classifier may use the identifiers of the trained classifier to determine the sentiment of opinion data for the target domain.

Sentiment classification using out of domain data

A smart user-centric information aggregation system allows a user to define a region of content displayed in a display of a device and performs information aggregation on behalf of the user. The smart user-centric information aggregation system searches, aggregates and groups information related to content included in the region of content for the user while the user can continue to perform his/her original course of actions without interruption. After finding information related to the desired content, the smart user-centric information aggregation system may notify the user and present the found information to the user upon receiving confirmation from the user. The smart user-centric information aggregation system may continue to find new related information and update the presentation with the newly found information periodically, in some instances without user intervention or input.

Smart user-centric information aggregation

A method for identifying transactional queries includes associating user queries with forms clicks on by users who employ a search engine to place the queries during query sessions. A score is assigned to each user query. The score reflects a likelihood that the respective query is a transactional query. The query is classified as a transactional query if the score exceeds a threshold value.

Classification of transactional queries based on identification of forms

A user may perform an image search on an object shown in an image. The user may use a mobile device to display an image. In response to displaying the image, the client device may send the image to a visual search system for image segmentation. Upon receiving a segmented image from the visual search system, the client device may display the segmented image to the user who may select one or more segments including an object of interest to instantiate a search. The visual search system may formulate a search query based on the one or more selected segments and perform a search using the search query. The visual search system may then return search results to the client device for display to the user.

Gesture-based visual search

Disclosed are systems and methods for extracting semantic-based keywords through mining word semantics using an online encyclopedia's taxonomy. Described is the use a semantic bipartite graph that relates candidate keywords and topics.

Enhancing keyword advertising using online encyclopedia semantics

A method of ranking a plurality of products includes obtaining a numerical user score for each of the plurality of products, calculating an opinion score for each of the plurality of products for which a written comparison sentiment applies, determining a final score by combining the numerical user rating and the opinion score for each of the plurality of products, and ranking the plurality of products based on the final score. The opinion score is derived from one or more written comparison sentiments containing a first product name and a second product name. In another aspect, a computer readable medium has instructions stored thereon which, when executed, cause a computer to perform a method of ranking a plurality of products including at least a first product and a second product.

Ranking products by mining comparison sentiment

Techniques for identifying attributes in a sentence and determining a number of attributes to be associated with the sentence is described. An attribute identification (AI) framework comprises an offline training portion, an online prediction portion, and an AI algorithm module. The offline training portion utilizes the relationships between attributes within sentences input to the offline training portion to improve attribute identification of the AI algorithm module. The online prediction portion predicts, for each sentence input, the attributes of the sentence and the number of attributes the sentence is associated with by employing the AI algorithm module.

Smart attribute classification (SAC) for online reviews

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Beijing, China

Jian-Tao Sun