토픽모델링을 이용한 주요 키워드 간 관계 분석
- 주제(키워드) 토픽모델링 , 연관성규칙 , 문서클러스터링 , 계층적군집
- 발행기관 고려대학교 대학원
- 지도교수 이홍철
- 발행년도 2018
- 학위수여년월 2018. 2
- 학위구분 석사
- 학과 대학원 산업경영공학과
- 원문페이지 34 p
- 실제URI http://www.dcollection.net/handler/korea/000000081026
- 본문언어 한국어
- 제출원본 000045932287
초록/요약
In this paper, we propose a dynamic document classification method which breaks away from existing document classification method with artificial categorization rules focusing on suppliers and has changing categorization rules according to users’ needs or social trends. The core of this dynamic document classification method lies in the fact that it creates classification criteria real-time by using topic modeling techniques without standardized category rules, which does not force users to use unnecessary frames. In addition, it can also search the details through the relevance analysis by calculating the relationship between the words that is difficult to grasp by word frequency alone. Rather than for logical and systematic documents, this method proposed can be used more effectively for situation analysis and retrieving information of unstructured data which do not fit the category of existing classification such as VOC (Voice Of Customer), SNS and customer reviews of Internet shopping malls and it can react to users’ needs flexibly. In addition, it has no process of selecting the classification rules by the suppliers and in case there is a misclassification, it requires no manual work, which reduces unnecessary workload.
more목차
목차
1. 서론 1
1.1 연구배경 1
1.2 연구목적 4
2. 이론적 배경 5
2.1 문서 분류 5
2.2 토픽 모델링 6
2.3 연관성 규칙 8
3. 연구방법 10
3.1 실험 절차 10
3.2 실험 환경 12
3.3 실험 결과 13
3.3.1 후보키워드 생성 및 키워드 설정 13
3.3.2 대표키워드 선정 및 단어 관계 생성 15
4. 사례 연구 20
5. 결론 및 향후방안 21
참고문헌 23
