Patents by Inventor Gayle McElvain
Gayle McElvain 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: 20240086446Abstract: Aspects of the present disclosure provide systems, methods, apparatus, and computer-readable storage media that support identifying overruled in part content based on citationally related content. The most relevant passage, content, paragraph and the like, may be identified out of the citationally related content by providing extracted features as input data to trained machine learning classifiers to generate probability values. A ranking approach may be used where the content or paragraphs of an opinion may be selected as most relevant based on the generated probability values. In some implementations, a machine learning modeling approach may be used for both the overruling side and the overruled side of the content by leveraging different features and the relationship between the overruling document and the overruled document.Type: ApplicationFiled: September 13, 2023Publication date: March 14, 2024Inventors: Gayle McElvain, Dhivya Infant Chinnappa, Travis Jon Denneson, Diane Lynne Erickson
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Patent number: 11886813Abstract: A system and method of operating a system for automatically punctuating text using non-recurrent neural networks is disclosed. The system and method at least: applying a text string to a first component of a non-recurrent neural network trained to generate one or more contextualized vectors, wherein the first component determines the contextualized vectors by processing each word in the text string in parallel with one another; applying the contextualized vectors to a second component of the non-recurrent neural network trained to generate a set of probability values for each word in the text string, wherein the second component determines the set of probability values by processing the contextualized vectors in parallel with one another; and transmitting the set of probability values to a text generation engine to generate a formatted text string based on the set of probability values.Type: GrantFiled: September 24, 2020Date of Patent: January 30, 2024Assignee: Capital One Services, LLCInventors: Maury Courtland, Adam Faulkner, Gayle McElvain
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Patent number: 11615492Abstract: The present disclosure relates to systems and methods for analyzing citationally related content and identifying, based on the analysis, a risk of impliedly overruled content. Embodiments provide for receiving case law data from a document source, for extracting a case triple that includes a first case overruling or abrogating a second case, and a third case citationally related to the second case. Features may be generated from case triple, such as natural processing language features comparing the language in the various cases of the triple, and feeding the generated features to a main classifier. In embodiments, the main classifier classifies the case triple into a class indicating the risk probability that the second case is impliedly overruled by the first case.Type: GrantFiled: May 14, 2019Date of Patent: March 28, 2023Assignee: Thomson Reuters Enterprise Centre GmbHInventors: Julian Brooke, Kanika Madan, Hector Martinez Alonso, Afsaneh Fazly, Tonya Custis, Isabelle Moulinier, Gayle McElvain, Diane Erickson, Khaled Ammar
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Publication number: 20220383867Abstract: Embodiments disclosed are directed to a computing system that performs steps to automatically generate fine-grained call reasons from customer service call transcripts. The computing system extracts, using a natural language processing (NLP) technique, a set of events from a set of text strings of speaker turns. The computing system then identifies a set of clusters of events based on the set of events and labels each cluster of events in the set of clusters of events to generate a set of labeled clusters of events. Subsequently, the computing system assigns each event in the set of events to a respective labeled cluster of events in the set of labeled clusters of events.Type: ApplicationFiled: September 8, 2021Publication date: December 1, 2022Applicant: Capital One Services, LLCInventors: Adam FAULKNER, Gayle McELVAIN, John QUI
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Publication number: 20210382878Abstract: The present disclosure relates to systems and methods for generating contextually, grammatically, and conversationally correct answers to input questions. Embodiments provide for linguistic and syntactic structure analysis of a submitted question in order to determine whether the submitted question may be answered by at least one headnote. The question is then further analyzed to determine more details about the intent and context of the question. A federated search process, based on the linguistic and syntactic structure analysis, and the additional analysis of the question is used to identify candidate question-answer pairs from a corpus of previously created headnotes. Machine learning models are used to analyze the candidate question-answer pairs, additional rules are applied to rank the candidate answers, and dynamic thresholds are applied to identify the best potential answers to provide to a user as a response to the submitted question.Type: ApplicationFiled: August 16, 2021Publication date: December 9, 2021Inventors: Gayle McElvain, Tonya Custis, Matthew A. Surprenant, Erik Lindberg
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Publication number: 20210319176Abstract: A system and method of operating a system for automatically punctuating text using non-recurrent neural networks is disclosed. The system and method at least: applying a text string to a first component of a non-recurrent neural network trained to generate one or more contextualized vectors, wherein the first component determines the contextualized vectors by processing each word in the text string in parallel with one another; applying the contextualized vectors to a second component of the non-recurrent neural network trained to generate a set of probability values for each word in the text string, wherein the second component determines the set of probability values by processing the contextualized vectors in parallel with one another; and transmitting the set of probability values to a text generation engine to generate a formatted text string based on the set of probability values.Type: ApplicationFiled: September 24, 2020Publication date: October 14, 2021Applicant: Capital One Services, LLCInventors: Maury COURTLAND, Adam FAULKNER, Gayle McELVAIN
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Patent number: 11106664Abstract: The present disclosure relates to systems and methods for generating contextually, grammatically, and conversationally correct answers to input questions. Embodiments provide for linguistic and syntactic structure analysis of a submitted question in order to determine whether the submitted question may be answered by at least one headnote. The question is then further analyzed to determine more details about the intent and context of the question. A federated search process, based on the linguistic and syntactic structure analysis, and the additional analysis of the question is used to identify candidate question-answer pairs from a corpus of previously created headnotes. Machine learning models are used to analyze the candidate question-answer pairs, additional rules are applied to rank the candidate answers, and dynamic thresholds are applied to identify the best potential answers to provide to a user as a response to the submitted question.Type: GrantFiled: May 2, 2019Date of Patent: August 31, 2021Assignee: Thomson Reuters Enterprise Centre GmbHInventors: Gayle McElvain, Tonya Custis, Matthew A. Surprenant, Erik Lindberg
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Publication number: 20190347748Abstract: The present disclosure relates to systems and methods for analyzing citationally related content and identifying, based on the analysis, a risk of impliedly overruled content. Embodiments provide for receiving case law data from a document source, for extracting a case triple that includes a first case overruling or abrogating a second case, and a third case citationally related to the second case. Features may be generated from case triple, such as natural processing language features comparing the language in the various cases of the triple, and feeding the generated features to a main classifier. In embodiments, the main classifier classifies the case triple into a class indicating the risk probability that the second case is impliedly overruled by the first case.Type: ApplicationFiled: May 14, 2019Publication date: November 14, 2019Inventors: Julian Brooke, Kanika Madan, Hector Martinez Alonso, Afsaneh Fazly, Tonya Custis, Isabelle Moulinier, Gayle McElvain, Diane Erickson, Khaled Ammar
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Publication number: 20190340172Abstract: The present disclosure relates to systems and methods for generating contextually, grammatically, and conversationally correct answers to input questions. Embodiments provide for linguistic and syntactic structure analysis of a submitted question in order to determine whether the submitted question may be answered by at least one headnote. The question is then further analyzed to determine more details about the intent and context of the question. A federated search process, based on the linguistic and syntactic structure analysis, and the additional analysis of the question is used to identify candidate question-answer pairs from a corpus of previously created headnotes. Machine learning models are used to analyze the candidate question-answer pairs, additional rules are applied to rank the candidate answers, and dynamic thresholds are applied to identify the best potential answers to provide to a user as a response to the submitted question.Type: ApplicationFiled: May 2, 2019Publication date: November 7, 2019Inventors: Gayle McElvain, Tonya Custis, Matthew A. Surprenant, Erik Lindberg
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Patent number: 8504392Abstract: Systems and methods can mine structured clinical event data in an electronic health record (EHR) system to determine patient outcomes. Mining the structured clinical event data instead of or in addition to mining discharge summaries can increase the accuracy of patient outcome identification. Sophisticated language models can be used to extract outcomes from discharge summaries while also inferring outcomes from cues or hints contained in the structured clinical event data. For example, the clinical event data can include information regarding treatments and medications prescribed by clinicians to specifically manage patient complications; thus, presence or absence of relevant treatments in the clinical event data can provide independent indicators to disambiguate cases where current language processing approaches fail.Type: GrantFiled: November 11, 2011Date of Patent: August 6, 2013Assignee: The Board of Trustees of the Leland Stanford Junior UniversityInventors: Suchi Saria, Gayle McElvain, Anand K. Rajani, Anna A. Penn, Daphne L. Koller
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Publication number: 20120290319Abstract: Systems and methods can mine structured clinical event data in an electronic health record (EHR) system to determine patient outcomes. Mining the structured clinical event data instead of or in addition to mining discharge summaries can increase the accuracy of patient outcome identification. Sophisticated language models can be used to extract outcomes from discharge summaries while also inferring outcomes from cues or hints contained in the structured clinical event data. For example, the clinical event data can include information regarding treatments and medications prescribed by clinicians to specifically manage patient complications; thus, presence or absence of relevant treatments in the clinical event data can provide independent indicators to disambiguate cases where current language processing approaches fail.Type: ApplicationFiled: November 11, 2011Publication date: November 15, 2012Applicant: The Board of Trustees of the Leland Stanford Junior UniversityInventors: Suchi Saria, Gayle McElvain, Anand K. Rajani, Anna A. Penn, Daphne Koller