Patents by Inventor Alex Rubarkh
Alex Rubarkh 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: 20210232764Abstract: Aspects of the subject disclosure may include, for example, a process that performs a statistical, natural-language processing analysis on a group of text documents to determine a group of topics. The topics are determined according to parameters obtained by training on a sample of documents. One or more topics in a subset of topics are associated to each document, resulting in topic-document pairs. A bias is identified for each topic-document pair, and clusters of topics are created from the subset of topics. Each cluster of topics is determined from a value for each bias of each topic-document pair and from a frequency of occurrence of each topic. Each cluster is presentable according to a corresponding image configuration based on all or a subset of the bias dimensions and the frequency of occurrence of topics in a cluster that distinguishes the cluster from other clusters. Other embodiments are disclosed.Type: ApplicationFiled: April 16, 2021Publication date: July 29, 2021Applicant: AT&T Intellectual Property I, L.P.Inventors: Pamela Bogdan, Gary Gressel, Gary Reser, Alex Rubarkh, Kenneth Shirley
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Patent number: 11010548Abstract: Aspects of the subject disclosure may include, for example, a process that performs a statistical, natural-language processing analysis on a group of text documents to determine a group of topics. The topics are determined according to parameters obtained by training on a sample of documents. One or more topics in a subset of topics are associated to each document, resulting in topic-document pairs. A bias is identified for each topic-document pair, and clusters of topics are created from the subset of topics. Each cluster of topics is determined from a value for each bias of each topic-document pair and from a frequency of occurrence of each topic. Each cluster is presentable according to a corresponding image configuration based on all or a subset of the bias dimensions and the frequency of occurrence of topics in a cluster that distinguishes the cluster from other clusters. Other embodiments are disclosed.Type: GrantFiled: April 3, 2020Date of Patent: May 18, 2021Assignee: AT&T Intellectual Property I, L.P.Inventors: Pamela Bogdan, Gary Gressel, Gary Reser, Alex Rubarkh, Kenneth Shirley
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Publication number: 20200234005Abstract: Aspects of the subject disclosure may include, for example, a process that performs a statistical, natural-language processing analysis on a group of text documents to determine a group of topics. The topics are determined according to parameters obtained by training on a sample of documents. One or more topics in a subset of topics are associated to each document, resulting in topic-document pairs. A bias is identified for each topic-document pair, and clusters of topics are created from the subset of topics. Each cluster of topics is determined from a value for each bias of each topic-document pair and from a frequency of occurrence of each topic. Each cluster is presentable according to a corresponding image configuration based on all or a subset of the bias dimensions and the frequency of occurrence of topics in a cluster that distinguishes the cluster from other clusters. Other embodiments are disclosed.Type: ApplicationFiled: April 3, 2020Publication date: July 23, 2020Applicant: AT&T Intellectual Property I, L.P.Inventors: Pamela Bogdan, Gary Gressel, Gary Reser, Alex Rubarkh, Kenneth Shirley
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Patent number: 10642932Abstract: Aspects of the subject disclosure may include, for example, a process that performs a statistical, natural-language processing analysis on a group of text documents to determine a group of topics. The topics are determined according to parameters obtained by training on a sample of documents. One or more topics in a subset of topics are associated to each document, resulting in topic-document pairs. A bias is identified for each topic-document pair, and clusters of topics are created from the subset of topics. Each cluster of topics is determined from a value for each bias of each topic-document pair and from a frequency of occurrence of each topic. Each cluster is presentable according to a corresponding image configuration based on all or a subset of the bias dimensions and the frequency of occurrence of topics in a cluster that distinguishes the cluster from other clusters. Other embodiments are disclosed.Type: GrantFiled: March 12, 2019Date of Patent: May 5, 2020Assignee: AT&T Intellectual Property I, L.P.Inventors: Pamela A. M. Bogdan, Gary Gressel, Gary Reser, Alex Rubarkh, Kenneth Shirley
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Publication number: 20190272320Abstract: Aspects of the subject disclosure may include, for example, a process that performs a statistical, natural-language processing analysis on a group of text documents to determine a group of topics. The topics are determined according to parameters obtained by training on a sample of documents. One or more topics in a subset of topics are associated to each document, resulting in topic-document pairs. A bias is identified for each topic-document pair, and clusters of topics are created from the subset of topics. Each cluster of topics is determined from a value for each bias of each topic-document pair and from a frequency of occurrence of each topic. Each cluster is presentable according to a corresponding image configuration based on all or a subset of the bias dimensions and the frequency of occurrence of topics in a cluster that distinguishes the cluster from other clusters. Other embodiments are disclosed.Type: ApplicationFiled: March 12, 2019Publication date: September 5, 2019Applicant: AT&T Intellectual Property I, L.P.Inventors: Pamela A. M. Bogdan, Gary Gressel, Gary Reser, Alex Rubarkh, Kenneth Shirley
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Patent number: 10275444Abstract: Aspects of the subject disclosure may include, for example, a computer that performs a statistical natural language processing analysis on a plurality of text documents to determine a plurality of topics, creates a proper subset of topics from the plurality of topics, based on user input, maps one or more topics in the proper subset of topics to each document in the plurality of text documents, thereby creating a plurality of topic-document pairs, identifies n-dimensions of bias for each topic-document pair from the text, creates clusters of topics from the proper subset of topics, and generates presentable content depicting each cluster of the clusters of topics according to a corresponding image configuration. The topics and n-dimensions of bias data can be further analyzed with co-collected structured data for statistical relationships.Type: GrantFiled: July 15, 2016Date of Patent: April 30, 2019Assignee: AT&T INTELLECTUAL PROPERTY I, L.P.Inventors: Pamela Bogdan, Gary Gressel, Gary Reser, Alex Rubarkh, Kenneth Shirley
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Publication number: 20180018316Abstract: Aspects of the subject disclosure may include, for example, a computer that performs a statistical natural language processing analysis on a plurality of text documents to determine a plurality of topics, creates a proper subset of topics from the plurality of topics, based on user input, maps one or more topics in the proper subset of topics to each document in the plurality of text documents, thereby creating a plurality of topic-document pairs, identifies n-dimensions of bias for each topic-document pair from the text, creates clusters of topics from the proper subset of topics, and generates presentable content depicting each cluster of the clusters of topics according to a corresponding image configuration. The topics and n-dimensions of bias data can be further analyzed with co-collected structured data for statistical relationships.Type: ApplicationFiled: July 15, 2016Publication date: January 18, 2018Inventors: Pamela Bogdan, Gary Gressel, Gary Reser, Alex Rubarkh, Kenneth Shirley