Patents by Inventor Qifa Ke
Qifa Ke has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11200269Abstract: Examples of the present disclosure describe systems and methods relating to generating relevance scores for one or more words of a passage which is an answer to a natural language query. For instance, a passage extracted from a highly relevant electronic file along with the query may encoded and augmented to generate a multi-dimensional, augmented semantic vectors using recurring neural networks. The augmented semantic vectors along with a multi-dimensional vector that represent words of the passage may be decoded to generate relevance scores for one or more words of the passage, based on levels of relevance to the query.Type: GrantFiled: June 15, 2017Date of Patent: December 14, 2021Assignee: Microsoft Technology Licensing, LLCInventors: Qifa Ke, Frank Torsten Bernd Seide, Qi Liu, Rajanala Sai Krishna Sravanthi
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Patent number: 11068474Abstract: Systems and techniques for sequence to sequence conversational query understanding are described herein. A query may be received that includes multiple words. It may be identified that the query is to be reformulated based on an attention value for an attention word in the query. Relationships may be determined among words of the query and words in a previously submitted query and words in results from the previously submitted query. The query may be reformulated based on the relationships. The reformulated query may be employed to retrieve query results.Type: GrantFiled: March 12, 2018Date of Patent: July 20, 2021Assignee: Microsoft Technology Licensing, LLCInventors: Xiaochuan Ni, Jiarui Ren, Manish Malik, Qifa Ke
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Patent number: 10572598Abstract: Examples of the present disclosure describe systems and methods relating to generating a relevance score on a given natural language answer to a natural language query for ranking the answer among other answers for the query, while generating a summary passage and a likely query to the given passage. For instance, multi-layered, recurrent neural networks may be used to encode the query and the passage, along with a multi-layered neural network for information retrieval features, to generate a relevant score for the passage. A multi-layered, recurrent neural network with soft attention and sequence-to-sequence learning task may be used as a decoder to generate a summary passage. A common encoding neural network may be employed to encode the passage for the ranking and the summarizing, in order to present concise and accurate natural language answers to the query.Type: GrantFiled: February 25, 2019Date of Patent: February 25, 2020Assignee: Microsoft Technology Licensing, LLCInventors: Doran Chakraborty, Manish Malik, Qifa Ke, Jonathan R. Tiao
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Patent number: 10534780Abstract: Non-limiting examples of the present disclosure describe a unified ranking model that may be used by a plurality of entry points to return ranked results in response to received query data. The unified ranking model is provided as a service for a plurality of entry points. A query is received from an entry point of the plurality of entry points. Results data for the query data is retrieved. A unified ranking model is executed to rank the results data. Execution of the unified ranking model manipulates feature data of the unified ranking model based on user context signals associated with the received query data and acquired result retrieval signals corresponding with the retrieved results data. Execution of the unified ranking model generates ranked result data. Ranked results data is returned to the processing device corresponding with the entry point. Other examples are also described.Type: GrantFiled: October 28, 2015Date of Patent: January 14, 2020Assignee: Microsoft Technology Licensing, LLCInventors: Manish Malik, Qifa Ke, Rangan Majumder, Andreas Bode, Pushpraj Shukla, Yu Shi
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Publication number: 20190278857Abstract: Systems and techniques for sequence to sequence conversational query understanding are described herein. A query may be received that includes multiple words. It may be identified that the query is to be reformulated based on an attention value for an attention word in the query. Relationships may be determined among words of the query and words in a previously submitted query and words in results from the previously submitted query. The query may be reformulated based on the relationships. The reformulated query may be employed to retrieve query results.Type: ApplicationFiled: March 12, 2018Publication date: September 12, 2019Inventors: Xiaochuan Ni, Jiarui Ren, Manish Malik, Qifa Ke
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Publication number: 20190188262Abstract: Examples of the present disclosure describe systems and methods relating to generating a relevance score on a given natural language answer to a natural language query for ranking the answer among other answers for the query, while generating a summary passage and a likely query to the given passage. For instance, multi-layered, recurrent neural networks may be used to encode the query and the passage, along with a multi-layered neural network for information retrieval features, to generate a relevant score for the passage. A multi-layered, recurrent neural network with soft attention and sequence-to-sequence learning task may be used as a decoder to generate a summary passage. A common encoding neural network may be employed to encode the passage for the ranking and the summarizing, in order to present concise and accurate natural language answers to the query.Type: ApplicationFiled: February 25, 2019Publication date: June 20, 2019Applicant: Microsoft Technology Licensing, LLCInventors: Doran CHAKRABORTY, Manish MALIK, Qifa KE, Jonathan R. TIAO
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Patent number: 10255273Abstract: Examples of the present disclosure describe systems and methods relating to generating a relevance score on a given natural language answer to a natural language query for ranking the answer among other answers for the query, while generating a summary passage and a likely query to the given passage. For instance, multi-layered, recurrent neural networks may be used to encode the query and the passage, along with a multi-layered neural network for information retrieval features, to generate a relevant score for the passage. A multi-layered, recurrent neural network with soft attention and sequence-to-sequence learning task may be used as a decoder to generate a summary passage. A common encoding neural network may be employed to encode the passage for the ranking and the summarizing, in order to present concise and accurate natural language answers to the query.Type: GrantFiled: June 15, 2017Date of Patent: April 9, 2019Assignee: Microsoft Technology Licensing, LLCInventors: Doran Chakraborty, Manish Malik, Qifa Ke, Jonathan R. Tiao
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Patent number: 10192279Abstract: A Mixed Media Reality (MMR) system and associated techniques are disclosed. The MMR system provides mechanisms for forming a mixed media document that includes media of at least two types (e.g., printed paper as a first medium and digital content and/or web link as a second medium). The present invention provides systems, methods, and computer program products for modifying documents for shared use, and for collaborative discussion of shared documents. Captured digital images of documents or portions associated with a user are received, along with modifications to the images. Documents are recognized from the captured digital images, and the modifications to the images are applied to the documents. Alternatively, captured digital images of documents are received, and the documents are recognized along with a hotspot in the document. The user is authenticated to a website associated with the hotspot, and is provided access to an associated multimedia repository.Type: GrantFiled: March 31, 2008Date of Patent: January 29, 2019Assignee: Ricoh Co., Ltd.Inventors: Berna Erol, Jonathan J. Hull, Hidenobu Kishi, Qifa Ke, Jorge Moraleda
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Publication number: 20190012373Abstract: Conversational or multi-turn question understanding using web intelligence is provided. An intelligent query understanding system is provided for receiving a context-dependent query from a user, obtaining contextual information related to the context-dependent query, and reformatting the context-dependent query as one or more reformulations based on the contextual information. The intelligent query understanding system is further operative to query a search engine with the one or more reformulations, receive one or more candidate results, and select a highest ranked reformulation based on the candidate results. The system can provide the highest ranked reformulation of the highest ranked reformulation as a response.Type: ApplicationFiled: July 10, 2017Publication date: January 10, 2019Applicant: Microsoft Technology Licensing, LLCInventors: Manish Malik, Jiarui Ren, Qifa Ke
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Patent number: 10169453Abstract: A summary of a document is generated in near real time. In aspects, an indication to summarize the document is received and the document is processed to generate a summary. For instance, processing includes extracting sentences from the document and generating a plurality of candidate passages from the extracted sentences. Features are extracted from each of the plurality of candidate passages and each candidate passage is ranked based at least in part on the extracted features. High-ranking candidate passages are considered likely to be important and/or representative of the document. A summary of the document is generated including one or more of the high-ranking candidate passages. The summary includes portions of the document that are considered important and/or representative of the document, so a user may review the summary in lieu of reading the entire document.Type: GrantFiled: March 28, 2016Date of Patent: January 1, 2019Assignee: Microsoft Technology Licensing, LLCInventors: Gang Luo, Qi Liu, Krishna Sravanthi Rajanala Sai, Dario Bigongiari, Qifa Ke, Oana Diana Nicolov, Srinivas Vadrevu
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Publication number: 20180365321Abstract: Examples of the present disclosure describe systems and methods relating to generating relevance scores for one or more words of a passage which is an answer to a natural language query. For instance, a passage extracted from a highly relevant electronic file along with the query may encoded and augmented to generate a multi-dimensional, augmented semantic vectors using recurring neural networks. The augmented semantic vectors along with a multi-dimensional vector that represent words of the passage may be decoded to generate relevance scores for one or more words of the passage, based on levels of relevance to the query.Type: ApplicationFiled: June 15, 2017Publication date: December 20, 2018Applicant: Microsoft Technology Licensing, LLCInventors: Qifa KE, Frank Torsten Bernd SEIDE, Qi LIU, Rajanala Sai Krishna SRAVANTHI
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Publication number: 20180365220Abstract: Examples of the present disclosure describe systems and methods relating to generating a relevance score on a given natural language answer to a natural language query for ranking the answer among other answers for the query, while generating a summary passage and a likely query to the given passage. For instance, multi-layered, recurrent neural networks may be used to encode the query and the passage, along with a multi-layered neural network for information retrieval features, to generate a relevant score for the passage. A multi-layered, recurrent neural network with soft attention and sequence-to-sequence learning task may be used as a decoder to generate a summary passage. A common encoding neural network may be employed to encode the passage for the ranking and the summarizing, in order to present concise and accurate natural language answers to the query.Type: ApplicationFiled: June 15, 2017Publication date: December 20, 2018Applicant: Microsoft Technology Licensing, LLCInventors: Doran CHAKRABORTY, Manish MALIK, Qifa KE, Jonathan R. TIAO
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Publication number: 20170277668Abstract: A summary of a document is generated in near real time. In aspects, an indication to summarize the document is received and the document is processed to generate a summary. For instance, processing includes extracting sentences from the document and generating a plurality of candidate passages from the extracted sentences. Features are extracted from each of the plurality of candidate passages and each candidate passage is ranked based at least in part on the extracted features. High-ranking candidate passages are considered likely to be important and/or representative of the document. A summary of the document is generated including one or more of the high-ranking candidate passages. The summary includes portions of the document that are considered important and/or representative of the document, so a user may review the summary in lieu of reading the entire document.Type: ApplicationFiled: March 28, 2016Publication date: September 28, 2017Applicant: Microsoft Technology Licensing, LLCInventors: Gang Luo, Qi Liu, Krishna Sravanthi Rajanala Sai, Dario Bigongiari, Qifa Ke, Oana Diana Nicolov, Srinivas Vadrevu
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Patent number: 9710493Abstract: A set of data points is divided into a plurality of subsets of data points. A set of cluster closures is generated based at least in part on the subset of data points. Each cluster closure envelopes a corresponding cluster of a set of clusters and is comprised of data points of the enveloped cluster and data points neighboring the enveloped cluster. A k-Means approximator iteratively assigns data points to a cluster of the set of clusters and updates a set of cluster centroids corresponding to the set of clusters. The k-Means approximator assigns data points based at least in part on the set of cluster closures.Type: GrantFiled: March 8, 2013Date of Patent: July 18, 2017Assignee: Microsoft Technology Licensing, LLCInventors: Jingdong Wang, Qifa Ke, Shipeng Li, Jing Wang
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Patent number: 9710491Abstract: Image descriptor identifiers are used for content-based search. A plurality of descriptors is determined for an image. The descriptors represent the content of the image at respective interest points identified in the image. The descriptors are mapped to respective descriptor identifiers. The image can thus be represented as a set of descriptor identifiers. A search is performed on an index using the descriptor identifiers as search elements. A method for efficiently searching the inverted index is also provided. Candidate images that include at least a predetermined number of descriptor identifiers that match those of the image are identified. The candidate images are ranked and at least a portion thereof are presented as content-based search results.Type: GrantFiled: November 2, 2009Date of Patent: July 18, 2017Assignee: Microsoft Technology Licensing, LLCInventors: Qifa Ke, Ming Liu, Yi Li
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Publication number: 20170124078Abstract: Non-limiting examples of the present disclosure describe a unified ranking model that may be used by a plurality of entry points to return ranked results in response to received query data. The unified ranking model is provided as a service for a plurality of entry points. A query is received from an entry point of the plurality of entry points. Results data for the query data is retrieved. A unified ranking model is executed to rank the results data. Execution of the unified ranking model manipulates feature data of the unified ranking model based on user context signals associated with the received query data and acquired result retrieval signals corresponding with the retrieved results data. Execution of the unified ranking model generates ranked result data. Ranked results data is returned to the processing device corresponding with the entry point. Other examples are also described.Type: ApplicationFiled: October 28, 2015Publication date: May 4, 2017Applicant: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Manish Malik, Qifa Ke, Rangan Majumder, Andreas Bode, Pushpraj Shukla, Yu Shi
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Publication number: 20170075985Abstract: A natural language query may be transformed to a transformed natural language while keeping sufficient semantic meaning such that the query may be transformed. A natural language query may be received by a computing device and sent to a natural language transformation model for transformation. The transformation may use a variety of techniques including stop word removal, stop structure removal, noun phrase/entity detection, key concept detection, dependency filtering. The techniques may be sequenced.Type: ApplicationFiled: September 16, 2015Publication date: March 16, 2017Applicant: Microsoft Technology Licensing, LLCInventors: Doran Chakraborty, Manish Malik, Qifa Ke, Miriam Rosenberg, Xinghua Lou
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Patent number: 9373029Abstract: The present invention uses invisible junctions which are a set of local features unique to every page of the electronic document to match the captured image to a part of an electronic document. The present invention includes: an image capture device, a feature extraction and recognition system and database. When an electronic document is printed, the feature extraction and recognition system captures an image of the document page. The features in the captured image are then extracted, indexed and stored in the database. Given a query image, the features in the query image are extracted and compared against those stored in the database to identify the query image. The feature extraction and recognition system of the present invention is integrated into a multifunction peripheral. This allows the feature extraction and recognition system to be used in conjunction with other modules to provide security and annotation applications.Type: GrantFiled: March 31, 2008Date of Patent: June 21, 2016Assignee: Ricoh Co., Ltd.Inventors: Jonathan J. Hull, Berna Erol, Shigeharu Uda, Qifa Ke
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Patent number: 9355179Abstract: Methods and computer-storage media having computer-executable instructions embodied thereon that facilitate refining query results using visual cues are provided. Query results are determined in response to an indication of a user query. One or more groups of query results are generated from the query results based on categories of query results that share similar features. Visual cues are associated with each of the query result groups. Visual cues, in association with query result groups, are presented to a user. Query results associated with a selected visual cue may be presented to a user. A refined user query may be generated based on a selected visual cue.Type: GrantFiled: September 24, 2010Date of Patent: May 31, 2016Assignee: Microsoft Technology Licensing, LLCInventors: Yu-Ting Kuo, Yi Li, Fang Wen, Qifa Ke, Jian Sun
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Patent number: 9286548Abstract: Product images are used in conjunction with textual descriptions to improve classifications of product offerings. By combining cues from both text and image descriptions associated with products, implementations enhance both the precision and recall of product description classifications within the context of web-based commerce search. Several implementations are directed to improving those areas where text-only approaches are most unreliable. For example, several implementations use image signals to complement text classifiers and improve overall product classification in situations where brief textual product descriptions use vocabulary that overlaps with multiple diverse categories. Other implementations are directed to using text and images “training sets” to improve automated classifiers including text-only classifiers.Type: GrantFiled: May 30, 2014Date of Patent: March 15, 2016Assignee: Microsoft Technology LicensingInventors: Anitha Kannan, Partha Pratim Talukdar, Nikhil Rasiwasia, Qifa Ke, Rakesh Agrawal