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논문 기본 정보

자료유형
학술저널
저자정보
Nayoung Yun (Kwangwoon University) Sangkyu Lim (Kwangwoon University) Seoyoung Hong (New York University) Jiwon Moon (Kwangwoon University) Hakjun Lee (Kwangwoon University) Sunmok Kim (Kwangwoon University) Heung-Jae Lee (Kwangwoon University) Ki-Baek Lee (Kwangwoon University)
저널정보
대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.11 No.4
발행연도
2022.8
수록면
248 - 254 (7page)
DOI
10.5573/IEIESPC.2022.11.4.248

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초록· 키워드

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This paper proposes a novel assist system for customer service representatives based on natural language processing (NLP). In the proposed system, an NLP model calculates the relationships between a question from a customer and all the questions in a given FAQ list. Based on the model’s calculation, the system will recommend several FAQs that are more similar to the customer’s question than the others in the FAQ list and then the representative responses, whether the recommended questions are actually similar to the customer’s question or not. Since these responses become the data for the NLP model’s next training, the NLP model’s accuracy can be incrementally enhanced by repetitive fine-tuning with the accumulated data. The experimental result shows that the proposed system can effectively help customer service representatives as well as incrementally improve via the automatically accumulated data.

목차

Abstract
1. Introduction
2. The Proposed System
3. Performance Evaluation
4. Conclusion
References

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