Patents by Inventor Sheetal Srivastava
Sheetal Srivastava 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: 11849342Abstract: A method and related system determine a localness measure that represents accessibility of a node connectiveness within a signed network. The method comprises, with a computer processor, receiving focus node (FN) information related to an FN of a graph representing the signed network, receiving neighbor node (NN) information related to a plurality of NNs in the signed network, and determining the localness measure based on the NN information and the FN information. The method and system also determine a harmony measure that represents importance of a node connectiveness within a signed network. The method comprises, with a computer processor, receiving source node (SN) information related to an SN of a graph representing the signed network, receiving destination node (DN) information related to a DN in the signed network, and determining the harmony measure based on the SN information and the DN information.Type: GrantFiled: December 7, 2020Date of Patent: December 19, 2023Assignee: International Business Machines CorporationInventors: Mandar Mutalikdesai, Ashish Rao, Kartikeya Vats, Sheetal Srivastava, Sandipto Neogi, Ojasvi Bhalerao
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Patent number: 11526707Abstract: One or more computer processors creating a plurality of k-hop neighborhood contextual subgraphs utilizing extracted labelled nodes from an input graph; compute an eigenvector centrality score for each node contained in each created subgraph in the plurality of k-hop neighborhood contextual subgraphs; propagate a label for each node in each subgraph in the plurality of k-hop neighborhood contextual subgraphs leveraging an aggregated mathematical decay function, preserving a topical context of the label; calculate an attributable prestige vector for each node in each subgraph in the plurality of k-hop neighborhood contextual subgraphs based on the propagated label and the computed eigenvector centrality score associated with each node in each subgraph in the plurality of k-hop neighborhood contextual subgraph; and unsupervised predict a subsequent label for one or more subsequent nodes, subgraphs, or graphs utilizing the calculated attributable prestige vectors for each node in each subgraph.Type: GrantFiled: July 2, 2020Date of Patent: December 13, 2022Assignee: International Business Machines CorporationInventors: Mandar Mutalikdesai, Sheetal Srivastava, Kartikeya Vats, Debasish Kanhar
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Patent number: 11366967Abstract: Systems and methods are described for generating learning roadmaps from unstructured information. The systems and methods may provide for extracting a plurality of named entities from one or more corpora of information, constructing a graph based on the named entities, inducing a subgraph from the graph based on a target named entity, wherein the subgraph includes a subset of the named entities, ordering the subset of the named entities based on the subgraph, and generating a learning roadmap for the target named entity based on the ordering.Type: GrantFiled: July 24, 2019Date of Patent: June 21, 2022Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Mandar Mutalikdesai, Rahul Reddy Nimmakayala, Ashish Rao, Sheetal Srivastava, Kartikeya Vats
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Publication number: 20220182857Abstract: A method and related system determine a localness measure that represents accessibility of a node connectiveness within a signed network. The method comprises, with a computer processor, receiving focus node (FN) information related to an FN of a graph representing the signed network, receiving neighbor node (NN) information related to a plurality of NNs in the signed network, and determining the localness measure based on the NN information and the FN information. The method and system also determine a harmony measure that represents importance of a node connectiveness within a signed network. The method comprises, with a computer processor, receiving source node (SN) information related to an SN of a graph representing the signed network, receiving destination node (DN) information related to a DN in the signed network, and determining the harmony measure based on the SN information and the DN information.Type: ApplicationFiled: December 7, 2020Publication date: June 9, 2022Inventors: Mandar Mutalikdesai, Ashish Rao, Kartikeya Vats, Sheetal Srivastava, Sandipto Neogi, Ojasvi Bhalerao
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Patent number: 11328124Abstract: Systems and methods are described for generating learning roadmaps from unstructured information. The systems and methods may provide for extracting a plurality of named entities from one or more corpora of information, constructing a graph based on the named entities, inducing a subgraph from the graph based on a target named entity, wherein the subgraph includes a subset of the named entities, ordering the subset of the named entities based on the subgraph, and generating a learning roadmap for the target named entity based on the ordering.Type: GrantFiled: July 24, 2019Date of Patent: May 10, 2022Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Mandar Mutalikdesai, Rahul Reddy Nimmakayala, Ashish Rao, Sheetal Srivastava, Kartikeya Vats
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Patent number: 11240118Abstract: A mixing pattern system for networks is provided. One or more nodes in a network are analyzed. Grouping the one or more nodes into one or more classes within the network. A computer device analyzes one or more transactions between the one or more nodes in the network that include nodes within similar or distinct classes of the one or more nodes. A computer device identifies one or more mixing patterns associated with one or more transactions between the one or more nodes.Type: GrantFiled: October 10, 2019Date of Patent: February 1, 2022Assignee: International Business Machines CorporationInventors: Mandar Mutalikdesai, Pranjal Srivastava, Sheetal Srivastava, Ratul Sarkar
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Publication number: 20220004826Abstract: One or more computer processors creating a plurality of k-hop neighborhood contextual subgraphs utilizing extracted labelled nodes from an input graph; compute an eigenvector centrality score for each node contained in each created subgraph in the plurality of k-hop neighborhood contextual subgraphs; propagate a label for each node in each subgraph in the plurality of k-hop neighborhood contextual subgraphs leveraging an aggregated mathematical decay function, preserving a topical context of the label; calculate an attributable prestige vector for each node in each subgraph in the plurality of k-hop neighborhood contextual subgraphs based on the propagated label and the computed eigenvector centrality score associated with each node in each subgraph in the plurality of k-hop neighborhood contextual subgraph; and unsupervised predict a subsequent label for one or more subsequent nodes, subgraphs, or graphs utilizing the calculated attributable prestige vectors for each node in each subgraph.Type: ApplicationFiled: July 2, 2020Publication date: January 6, 2022Inventors: Mandar Mutalikdesai, Sheetal Srivastava, Kartikeya Vats, Debasish Kanhar
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Patent number: 10984199Abstract: Sentiment analysis is targeted toward a specific subject of interest (or selected subjects) in a passage of natural language text. A dependency tree is generated for the passage, and subtrees are found that have sentiment polarities which contribute to the subject(s) of interest. A targeted sentiment score is computed for the subject(s) of interest based on sentiment expressed in those subtrees. Consecutively occurring nouns in the passage are collapsed into a noun phrase, as are possessives with ensuing nouns. The sentiment expressed in a given subtree can be modified using various linguistic heuristics. For example, sentiment polarity which is modified by a negation word may be inverted, sentiment polarity which is modified by an intensifying word may be increased, or sentiment polarity which is modified by a diluting word may be decreased.Type: GrantFiled: November 21, 2018Date of Patent: April 20, 2021Assignee: International Business Machines CorporationInventors: Mandar Mutalikdesai, Anagha M, Sheetal Srivastava, Lavina Durgani
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Publication number: 20210111964Abstract: A mixing pattern system for networks is provided. One or more nodes in a network are analyzed. Grouping the one or more nodes into one or more classes within the network. A computer device analyzes one or more transactions between the one or more nodes in the network that include nodes within similar or distinct classes of the one or more nodes. A computer device identifies one or more mixing patterns associated with one or more transactions between the one or more nodes.Type: ApplicationFiled: October 10, 2019Publication date: April 15, 2021Inventors: Mandar Mutalikdesai, Pranjal Srivastava, Sheetal Srivastava, Ratul Sarkar
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Patent number: 10963643Abstract: Sentiment analysis is targeted toward a specific subject of interest (or selected subjects) in a passage of natural language text. A dependency tree is generated for the passage, and subtrees are found that have sentiment polarities which contribute to the subject(s) of interest. A targeted sentiment score is computed for the subject(s) of interest based on sentiment expressed in those subtrees. Consecutively occurring nouns in the passage are collapsed into a noun phrase, as are possessives with ensuing nouns. The sentiment expressed in a given subtree can be modified using various linguistic heuristics. For example, sentiment polarity which is modified by a negation word may be inverted, sentiment polarity which is modified by an intensifying word may be increased, or sentiment polarity which is modified by a diluting word may be decreased.Type: GrantFiled: November 21, 2018Date of Patent: March 30, 2021Assignee: International Business Machines CorporationInventors: Mandar Mutalikdesai, Anagha M, Sheetal Srivastava, Lavina Durgani
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Publication number: 20210026921Abstract: Systems and methods are described for generating learning roadmaps from unstructured information. The systems and methods may provide for extracting a plurality of named entities from one or more corpora of information, constructing a graph based on the named entities, inducing a subgraph from the graph based on a target named entity, wherein the subgraph includes a subset of the named entities, ordering the subset of the named entities based on the subgraph, and generating a learning roadmap for the target named entity based on the ordering.Type: ApplicationFiled: July 24, 2019Publication date: January 28, 2021Inventors: MANDAR MUTALIKDESAI, RAHUL REDDY NIMMAKAYALA, ASHISH RAO, SHEETAL SRIVASTAVA, KARTIKEYA VATS
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Publication number: 20200159831Abstract: Sentiment analysis is targeted toward a specific subject of interest (or selected subjects) in a passage of natural language text. A dependency tree is generated for the passage, and subtrees are found that have sentiment polarities which contribute to the subject(s) of interest. A targeted sentiment score is computed for the subject(s) of interest based on sentiment expressed in those subtrees. Consecutively occurring nouns in the passage are collapsed into a noun phrase, as are possessives with ensuing nouns. The sentiment expressed in a given subtree can be modified using various linguistic heuristics. For example, sentiment polarity which is modified by a negation word may be inverted, sentiment polarity which is modified by an intensifying word may be increased, or sentiment polarity which is modified by a diluting word may be decreased.Type: ApplicationFiled: November 21, 2018Publication date: May 21, 2020Inventors: Mandar Mutalikdesai, Anagha M, Sheetal Srivastava, Lavina Durgani
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Publication number: 20200159830Abstract: Sentiment analysis is targeted toward a specific subject of interest (or selected subjects) in a passage of natural language text. A dependency tree is generated for the passage, and subtrees are found that have sentiment polarities which contribute to the subject(s) of interest. A targeted sentiment score is computed for the subject(s) of interest based on sentiment expressed in those subtrees. Consecutively occurring nouns in the passage are collapsed into a noun phrase, as are possessives with ensuing nouns. The sentiment expressed in a given subtree can be modified using various linguistic heuristics. For example, sentiment polarity which is modified by a negation word may be inverted, sentiment polarity which is modified by an intensifying word may be increased, or sentiment polarity which is modified by a diluting word may be decreased.Type: ApplicationFiled: November 21, 2018Publication date: May 21, 2020Inventors: Mandar Mutalikdesai, Anagha M, Sheetal Srivastava, Lavina Durgani