Invention Grant
- Patent Title: Extracting joint topic-sentiment models from text inputs
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Application No.: US16585201Application Date: 2019-09-27
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Publication No.: US11238243B2Publication Date: 2022-02-01
- Inventor: Suman Roy , Malladi Vijay Varma , Siddhartha Asthana , Madhvi Gupta , Ashish Chaturvedi
- Applicant: Optum Technology, Inc.
- Applicant Address: US MN Eden Prairie
- Assignee: Optum Technology, Inc.
- Current Assignee: Optum Technology, Inc.
- Current Assignee Address: US MN Eden Prairie
- Agency: Alston & Bird LLP
- Main IPC: G06F40/30
- IPC: G06F40/30 ; G06F40/56 ; G06K9/00 ; G16H15/00 ; G06F40/42 ; G06F40/279 ; G06F40/284 ; G06F40/295

Abstract:
There is a need for solutions for more effective and efficient natural language processing systems for short texts. This need can be addressed, for example, by a system configured to obtain an initial term-topic correlation data object for a plurality of digital documents, obtain a user-defined term-topic correlation data object for the plurality of digital documents, generate a refined term-topic correlation data object and a refined document-sentiment correlation data object for the plurality of digital documents based at least in part on the initial term-topic correlation data object and the user-defined term-topic correlation data object, obtain a user-defined document-topic correlation data object for the plurality of digital documents, and generate a refined document-topic correlation object for the plurality of digital documents based at least in part on the refined term-topic correlation data object and the user-defined document-topic correlation data object.
Public/Granted literature
- US20210097145A1 EXTRACTING JOINT TOPIC-SENTIMENT MODELS FROM TEXT INPUTS Public/Granted day:2021-04-01
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