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논문검색

RNN과 강화 학습을 이용한 자동 문서 제목 생성

원문정보

Automatic Document Title Generation with RNN and Reinforcement Learning

조성민, 김우생

피인용수 : 0(자료제공 : 네이버학술정보)

초록

영어

Lately, a large amount of textual data have been poured out of the Internet and the technology to refine them is needed. Most of these data are long text and often have no title. Therefore, in this paper, we propose a technique to combine the sequence-to-sequence model of RNN and the REINFORCE algorithm to generate the title of the long text automatically. In addition, the TextRank algorithm was applied to extract a summarized text to minimize information loss in order to protect the shortcomings of the sequence-to-sequence model in which an information is lost when long texts are used. Through the experiment, the techniques proposed in this study are shown to be superior to the existing ones.

목차

Abstract
1. 서론
2. 관련 연구
3. RNN과 강화 학습을 결합한 제목 생성 모델
3.1 추출 요약 모델
3.2 사전 학습
3.3 강화 학습을 적용한 모델
3.4 보상함수
4. 실험
5.결과 및 성능 평가
6. 결론 및 추후 연구
References

저자정보

  • 조성민 Sung-Min Cho. Graduate School of Computer Science, Kwangwoon University
  • 김우생 Wooseng Kim. Professor, School of Software, Kwangwoon University

참고문헌

자료제공 : 네이버학술정보

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