Patents by Inventor Ye-Yi Wang
Ye-Yi Wang 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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Publication number: 20160323398Abstract: Techniques for providing a people recommendation system for predicting and recommending relevant people (or other entities) to include in a conversation based on contextual indicators. In an exemplary embodiment, email recipient recommendations may be suggested based on contextual signals, e.g., project names, body text, existing recipients, current date and time, etc. In an aspect, a plurality of properties including ranked key phrases are associated with profiles corresponding to personal entities. Aggregated profiles are analyzed using first- and second-layer processing techniques. The recommendations may be provided to the user reactively, e.g., in response to a specific query by the user to the people recommendation system, or proactively, e.g., based on the context of what the user is currently working on, in the absence of a specific query by the user.Type: ApplicationFiled: July 22, 2015Publication date: November 3, 2016Inventors: Chenlei Guo, Jianfeng Gao, Xinying Song, Byungki Byun, Yelong Shen, Ye-Yi Wang, Brian D. Remick, Edward Thiele, Mohammed Aatif Ali, Marcus Gois, Xiaodong He, Jianshu Chen, Divya Jetley, Stephen Friesen
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Publication number: 20160321283Abstract: Techniques for providing a people recommendation system for predicting and recommending relevant people (or other entities) to include in a conversation. In an exemplary embodiment, a plurality of conversation boxes associated with communications between a user and target recipients, or between other users and recipients, are collected and stored as user history. During a training phase, the user history is used to train encoder and decoder blocks in a de-noising auto-encoder model. During a prediction phase, the trained encoder and decoder are used to predict one or more recipients for a current conversation box composed by the user, based on contextual and other signals extracted from the current conversation box. The predicted recipients are ranked using a scoring function, and the top-ranked individuals or entities may be recommended to the user.Type: ApplicationFiled: July 28, 2015Publication date: November 3, 2016Inventors: Yelong Shen, Xinying Song, Jianfeng Gao, Chenlei Guo, Byungki Byun, Ye-Yi Wang, Brian D. Remick, Edward Thiele, Mohammed Aatif Ali, Marcus Gois, Yang Zou, Mariana Stepp, Divya Jetley, Stephen Friesen
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Publication number: 20160239568Abstract: Intent determination as a service (IaaS) is disclosed. A third party application may be provided access to an IaaS service. The third party application and the IaaS system may exchange or be provided registration data and information that allow configuration of data and interfaces used in provision of IaaS to the third party application. A query received as input at the third party application may be sent to the IaaS system and the intent of a query may be determined and indicated in a query response sent back to the third party application. A third party application may also interface with a device client application integrated into the operating system of a device as part of accessing an IaaS system. Use of IaaS for queries associated with or relevant to third party applications may extend the capabilities of the third party applications and device client applications.Type: ApplicationFiled: February 13, 2015Publication date: August 18, 2016Applicant: Microsoft Technology Licensing, LLCInventors: Alan Packer, Ravi Bikkula, Ye-Yi Wang
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Patent number: 9336299Abstract: A user's search experience may be enhanced by providing additional content based upon an understanding of the user's intent. Query tagging, the assigning of semantic labels to terms within a query, is one technique that may be utilized to determine the context of a user's search query. Accordingly, as provided herein, a query tagging model may be updated using one or more stratified lexicons. A list data structure (e.g., lists of phrases obtained from web pages) and seed distribution data (e.g., pre-labeled probability data) may be used by a graph learning technique to obtain an expanded set of phrases and their respective probabilities of corresponding with particular lexicons (e.g., semantic class lexicons). The expanded set of phrases may be used to group phrases into stratified lexicons. The stratified lexicons may be used as features for updating and/or executing the query tagging model.Type: GrantFiled: April 20, 2009Date of Patent: May 10, 2016Assignee: Microsoft Technology Licensing, LLCInventors: Ye-Yi Wang, Xiao Li, Raphael Dominik Hoffmann
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Patent number: 9336298Abstract: 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.Type: GrantFiled: June 16, 2011Date of Patent: May 10, 2016Assignee: Microsoft Technology Licensing, LLCInventors: Shipeng Li, Ye-Yi Wang, Xiaochuan Ni, Jian-Tao Sun, Zheng Chen, Zhimin Zhang, Xiaolong Li, Xuedong Huang, Li Jiang
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Patent number: 9218412Abstract: A database having listings rather than long documents is searched using a term frequency-inverse document frequency (Tf/Idf) algorithm.Type: GrantFiled: May 10, 2007Date of Patent: December 22, 2015Assignee: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Ye-Yi Wang, Dong Yu, Yun-Cheng Ju, Alejandro Acero, Geoffrey G. Zweig
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Publication number: 20150293976Abstract: A search engine is described herein for providing search results based on a context in which a query has been submitted, as expressed by context information. The search engine operates by ranking a plurality of documents based on a consideration of the query, and based, in part, on a context concept vector and a plurality of document concept vectors, both generated using a deep learning model (such as a deep neural network). The context concept vector is formed by a projection of the context information into a semantic space using the deep learning model. Each document concept vector is formed by a projection of document information, associated with a particular document, into the same semantic space using the deep learning model. The ranking operates by favoring documents that are relevant to the context within the semantic space, and disfavoring documents that are not relevant to the context.Type: ApplicationFiled: April 14, 2014Publication date: October 15, 2015Inventors: Chenlei Guo, Jianfeng Gao, Ye-Yi Wang, Li Deng, Xiaodong He
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Patent number: 9116984Abstract: Automatically summarizing electronic communication conversation threads is provided. Electronic mails, text messages, tasks, questions and answers, meeting requests, calendar items, and the like are processed via a combination of natural language processing and heuristics. For a given conversation thread, for example, an electronic mail thread associated with a given task, a text summary of the thread is generated to highlight the most important text in the thread. The text summary is presented to a user in a visual user interface to allow the user to quickly understand the significance or relevance of the thread.Type: GrantFiled: June 28, 2011Date of Patent: August 25, 2015Assignee: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Nicholas Caldwell, Saliha Azzam, Diego Perez Del Carpio, Ye-Yi Wang, Yizheng Cai, Michael Gamon
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Patent number: 8880548Abstract: This patent application pertains to dynamic search interaction. One example includes an organizational component configured to obtain a search query from a user. The organizational component can also be configured to obtain related search queries. The organizational component can further be configured to organize the related search queries by topic and to estimate a relative likelihood that an intent of the user matches an individual topic. This example also includes an image generation component configured to cause the organized related search queries to be presented on a graphical user interface (GUI) in a manner that reflects the relative likelihood.Type: GrantFiled: February 17, 2010Date of Patent: November 4, 2014Assignee: Microsoft CorporationInventors: Ye-Yi Wang, Robert L. Rounthwaite, Scott K. Imig
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Patent number: 8843470Abstract: Systems and methods are provided for classifying a search query. A first group of query classifiers can be used to evaluate a query relative to various subject matter domains. The evaluation results from the first group of domain classifiers can then be used by a second group of meta-classifiers. The meta-classifiers are based on non-linear classification models. The meta-classifiers are associated with meta-classifier categories that may correspond to a domain or that may correspond to a plurality of domains. The assigned meta-classifier category for a query can be used in any convenient manner, such as by triggering additional uses of the search query to match images or other alternative types of documents, or such as by allowing a subject matter domain to be assigned to the query.Type: GrantFiled: October 5, 2012Date of Patent: September 23, 2014Assignee: Microsoft CorporationInventors: Xiaolong Li, Ye-Yi Wang
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Publication number: 20140279995Abstract: Methods, systems, and computer-readable media for query simplification are provided. A search engine executed by a server receives a query. In response, the search engine determines whether the query is a long or hard query. For long or hard queries, the search engine drops one or more terms based on search engine logs. The search engine may utilize statistical models like machine translation, condition random fields, or max entropy, to identify the terms that should be dropped. The search engine obtains search results for the simplified query and transmits the results to a user that provided the query.Type: ApplicationFiled: March 14, 2013Publication date: September 18, 2014Applicant: MICROSOFT CORPORATIONInventors: Ye-Yi Wang, Xiaodong He, Xiaolong Li, Shihao Ji, Bin Zhang
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Publication number: 20140236575Abstract: Structured web pages are accessed and parsed to obtain implicit annotation for natural language understanding tasks. Search queries that hit these structured web pages are automatically mined for information that is used to semantically annotate the queries. The automatically annotated queries may be used for automatically building statistical unsupervised slot filling models without using a semantic annotation guideline. For example, tags that are located on a structured web page that are associated with the search query may be used to annotate the query. The mined search queries may be filtered to create a set of queries that is in a form of a natural language query and/or remove queries that are difficult to parse. A natural language model may be trained using the resulting mined queries. Some queries may be set aside for testing and the model may be adapted using in-domain sentences that are not annotated.Type: ApplicationFiled: February 21, 2013Publication date: August 21, 2014Applicant: MICROSOFT CORPORATIONInventors: Gokhan Tur, Dilek Hakkani-Tur, Larry Heck, Minwoo Jeong, Ye-Yi Wang
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Patent number: 8793130Abstract: A method of generating a confidence measure generator is provided for use in a voice search system, the voice search system including voice search components comprising a speech recognition system, a dialog manager and a search system. The method includes selecting voice search features, from a plurality of the voice search components, to be considered by the confidence measure generator in generating a voice search confidence measure. The method includes training a model, using a computer processor, to generate the voice search confidence measure based on selected voice search features.Type: GrantFiled: March 23, 2012Date of Patent: July 29, 2014Assignee: Microsoft CorporationInventors: Ye-Yi Wang, Yun-Cheng Ju, Dong Yu
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Publication number: 20140101119Abstract: Systems and methods are provided for classifying a search query. A first group of query classifiers can be used to evaluate a query relative to various subject matter domains. The evaluation results from the first group of domain classifiers can then be used by a second group of meta-classifiers. The meta-classifiers are based on non-linear classification models. The meta-classifiers are associated with meta-classifier categories that may correspond to a domain or that may correspond to a plurality of domains. The assigned meta-classifier category for a query can be used in any convenient manner, such as by triggering additional uses of the search query to match images or other alternative types of documents, or such as by allowing a subject matter domain to be assigned to the query.Type: ApplicationFiled: October 5, 2012Publication date: April 10, 2014Applicant: MICROSOFT CORPORATIONInventors: Xiaolong Li, Ye-Yi Wang
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Patent number: 8589157Abstract: An automated “Voice Search Message Service” provides a voice-based user interface for generating text messages from an arbitrary speech input. Specifically, the Voice Search Message Service provides a voice-search information retrieval process that evaluates user speech inputs to select one or more probabilistic matches from a database of pre-defined or user-defined text messages. These probabilistic matches are also optionally sorted in terms of relevancy. A single text message from the probabilistic matches is then selected and automatically transmitted to one or more intended recipients. Optionally, one or more of the probabilistic matches are presented to the user for confirmation or selection prior to transmission. Correction or recovery of speech recognition errors avoided since the probabilistic matches are intended to paraphrase the user speech input rather than exactly reproduce that speech, though exact matches are possible.Type: GrantFiled: December 5, 2008Date of Patent: November 19, 2013Assignee: Microsoft CorporationInventors: Yun-Cheng Ju, Ye-Yi Wang
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Patent number: 8442828Abstract: A conditional model is used in spoken language understanding. One such model is a conditional random field model.Type: GrantFiled: March 17, 2006Date of Patent: May 14, 2013Assignee: Microsoft CorporationInventors: Ye-Yi Wang, Alejandro Acero, John Sie Yuen Lee, Milind V. Mahajan
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Patent number: 8407214Abstract: To construct a classifier, a data structure correlating queries to items identified by the queries is received, where the data structure contains initial labeled queries that have been labeled with respect to predetermined classes, and unlabeled queries that have not been labeled with respect to the predetermined classes. The data structure is used to label at least some of the unlabeled queries with respect to the predetermined classes. Queries in the data structure that have been labeled with respect to the predetermined classes are used as training data to train the classifier.Type: GrantFiled: June 25, 2008Date of Patent: March 26, 2013Assignee: Microsoft Corp.Inventors: Xiao Li, Ye-Yi Wang
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Publication number: 20130007648Abstract: Automatically detected and identified tasks and calendar items from electronic communications may be populated into one or more tasks applications and calendaring applications. Text content retrieved from one or more electronic communications may be extracted and parsed for determining whether keywords or terms contained in the parsed text may lead to a classification of the text content or part of the text content as a task. Identified tasks may be automatically populated into a tasks application. Similarly, text content from such sources may be parsed for keywords and terms that may be identified as indicating calendar items, for example, meeting requests. Identified calendar items may be automatically populated into a calendar application as a calendar entry.Type: ApplicationFiled: June 28, 2011Publication date: January 3, 2013Applicant: MICROSOFT CORPORATIONInventors: Michael Gamon, Saliha Azzam, Yizheng Cai, Nicholas Caldwell, Ye-Yi Wang
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Publication number: 20130006973Abstract: Automatically summarizing electronic communication conversation threads is provided. Electronic mails, text messages, tasks, questions and answers, meeting requests, calendar items, and the like are processed via a combination of natural language processing and heuristics. For a given conversation thread, for example, an electronic mail thread associated with a given task, a text summary of the thread is generated to highlight the most important text in the thread. The text summary is presented to a user in a visual user interface to allow the user to quickly understand the significance or relevance of the thread.Type: ApplicationFiled: June 28, 2011Publication date: January 3, 2013Applicant: MICROSOFT CORPORATIONInventors: Nicholas Caldwell, Saliha Azzam, Diego Perez Del Carpio, Ye-Yi Wang, Yizheng Cai, Michael Gamon
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Publication number: 20120323948Abstract: 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.Type: ApplicationFiled: June 16, 2011Publication date: December 20, 2012Applicant: MICROSOFT CORPORATIONInventors: SHIPENG LI, YE-YI WANG, XIAOCHUAN NI, JIAN-TAO SUN, ZHENG CHEN, ZHIMIN ZHANG, XIAOLONG LI, XUEDONG HUANG, LI JIANG