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US Patent 10943072 Contextual and intent based natural language processing system and method

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Is a
Patent
Patent
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Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
109430720
Patent Inventor Names
Gopinath Jaganmohan0
Date of Patent
March 9, 2021
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Patent Application Number
171051140
Date Filed
November 25, 2020
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Patent Citations Received
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US Patent 11501088 Techniques for generating natural language text customized to linguistic preferences of a user
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US Patent 11561998 Implementing a visual analytics intent language across multiple devices
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US Patent 11567967 Applying a visual analytics intent language to infer ambiguous or underspecified intent
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US Patent 12008013 Applying a visual analytics intent language to generate data visualizations
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US Patent 12094458 Multi-channel conversation processing
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US Patent 12111859 Enterprise generative artificial intelligence architecture
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US Patent 12135810 Dynamic user dashboard based on artificial intelligence techniques
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US Patent 11631052 Ad hoc supply chain community node
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...
Patent Primary Examiner
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Kevin Ky
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Patent abstract

Methods and systems are disclosed for an artificial intelligence (AI)-based, conversational insight and action platform for user context and intent-based natural language processing and data insight generation. Using artificial intelligence and semantic analysis techniques, a knowledge graph is generated from structured data, and a word embedding is generated from unstructured data. A semantic meaning is extracted from a user request, and at least one user attribute and context are determined. One or more entities and relationships on the knowledge graph that match the semantic meaning are determined, based on the user attribute, context, and the word embedding. A sequence of analytical instructions is generated from the matching results, and applied to the structured data to generate a data insight response to the user request. If no matches are found, similar entities and relationships are presented to the user, and user selections are used to further train the system.

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