Information processing device, information processing method, and computer program
A neural network model using phrases for corporate evaluation addresses inaccuracies in ESG scoring by focusing on contextual relevance and adaptability, ensuring precise corporate evaluation values.
Patent Information
- Application Number
- JP2024034858
- Authority / Receiving Office
- JP · JP
- Patent Type
- Patents
- Current Assignee / Owner
- Filing Date
- 2024-03-07
- Publication Date
- 2026-07-01
- Estimated Expiration
- 2044-03-07
AI Technical Summary
Existing corporate evaluation methods based on news article word frequency and similarity analysis lead to inaccurate ESG risk scores, especially for companies not frequently mentioned in the news, and repetitive word usage inflates scores.
A neural network-based corporate evaluation model using phrases of two or more words related to specific evaluation items, trained on fragment data, calculates relevance scores by incorporating context through BERT, and updates with frequently occurring relevant phrases.
Accurately calculates corporate evaluation values by considering contextual relevance and adaptability to changing trends, providing reliable ESG risk assessments.
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Abstract
Citation Information
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