Invention Grant
- Patent Title: Determining concept relationships in document collections utilizing a sparse graph recovery machine-learning model
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Application No.: US17833142Application Date: 2022-06-06
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Publication No.: US12159110B2Publication Date: 2024-12-03
- Inventor: Harsh Shrivastava , Maurice Diesendruck , Robin Abraham
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Agency: Ray Quinney & Nebeker
- Agent Christopher Hallstrom
- Main IPC: G06F40/295
- IPC: G06F40/295

Abstract:
The present disclosure relates to systems, methods, and computer-readable media for utilizing a concept graphing system to determine and provide relationships between concepts within document collections or corpora. For example, the concept graphing system can generate and utilize machine-learning models, such as a sparse graph recovery machine-learning model, to identify less-obvious correlations between concepts, including positive and negative concept connections, as well as provide these connections within a visual concept graph. Additionally, the concept graphing system can provide a visual concept graph that determines and displays concept correlations based on the input of a single concept, multiple concepts, or no concepts.
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Information query