토픽 식별성 향상을 위한 키워드 재구성 기법

• 영문명: Keyword Reorganization Techniques for Improving the Identifiability of Topics
• 발행기관: 한국IT서비스학회
• 저자명: 윤여일(Yeoil Yun) 김남규(Namgyu Kim)
• 간행물 정보: 『한국IT서비스학회지』한국IT서비스학회지 제18권 제4호, 135~149쪽, 전체 15쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2019.11.30

영문 초록

Recently, there are many researches for extracting meaningful information from large amount of text data. Among various applications to extract information from text, topic modeling which express latent topics as a group of keywords is mainly used. Topic modeling presents several topic keywords by term/topic weight and the quality of those keywords are usually evaluated through coherence which implies the similarity of those keywords. However, the topic quality evaluation method based only on the similarity of keywords has its limitations because it is difficult to describe the content of a topic accurately enough with just a set of similar words. In this research, therefore, we propose topic keywords reorganizing method to improve the identifiability of topics. To reorganize topic keywords, each document first needs to be labeled with one representative topic which can be extracted from traditional topic modeling. After that, classification rules for classifying each document into a corresponding label are generated, and new topic keywords are extracted based on the classification rules. To evaluated the performance our method, we performed an experiment on 1,000 news articles. From the experiment, we confirmed that the keywords extracted from our proposed method have better identifiability than traditional topic keywords.

목차

1. 서 론

2. 선행 연구

3. 제안 방법론

4. 실험

5. 결 론

키워드

Classification Rules Keywords Reorganization Text Mining opic Evaluation Topic Modeling