- P-ISSN1013-0799
- E-ISSN2586-2073
- KCI
텍스트 마이닝 기법을 이용한 컴퓨터공학 및 정보학 분야 연구동향 조사: DBLP의 학술회의 데이터를 중심으로
Investigation of Topic Trends in Computer and Information Science by Text Mining Techniques: From the Perspective of Conferences in DBLP
송성전 (연세대학교 문헌정보학과)
송민 (연세대학교)
Abstract
The goal of this paper is to explore the field of Computer and Information Science with the aid of text mining techniques by mining Computer and Information Science related conference data available in DBLP (Digital Bibliography & Library Project). Although studies based on bibliometric analysis are most prevalent in investigating dynamics of a research field, we attempt to understand dynamics of the field by utilizing Latent Dirichlet Allocation (LDA)-based multinomial topic modeling. For this study, we collect 236,170 documents from 353 conferences related to Computer and Information Science in DBLP. We aim to include conferences in the field of Computer and Information Science as broad as possible. We analyze topic modeling results along with datasets collected over the period of 2000 to 2011 including top authors per topic and top conferences per topic. We identify the following four different patterns in topic trends in the field of computer and information science during this period: growing (network related topics), shrinking (AI and data mining related topics), continuing (web, text mining information retrieval and database related topics), and fluctuating pattern (HCI, information system and multimedia system related topics).
- keywords
- 텍스트 마이닝, 토픽 모델링, 토픽 다이나믹스, 연구동향, text mining, topic modeling, DMR, topic dynamics, research trend
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