Identifying optimal feature sets in Text Categorization(TC) is crucial in terms of improving the effectiveness. In this study, experiments on feature expansion were conducted using author provided keyword sets and article titles from typical scientific journal articles. The tool used for expanding feature sets is WordNet, a lexical database for English words. Given a data set and a lexical tool, this study presented that feature expansion with synonymous relationship was significantly effective on improving the results of TC. The experiment results pointed out that when expanding feature sets with synonyms using on classifier names, the effectiveness of TC was considerably improved regardless of word sense disambiguation. 키워드: 자질선정, 의미기반, 문서범주화 WordNet, text categorization, semantics, feature selection, feature expansion * 이화여자대학교 사회과학대학 문헌정보학 조교수(echung@ewha.ac.kr) ■논문접수일자:2009년 8월 16일 ■최초심사일자:2009년 8월 20일 ■게재확정일자:2009년 8월 28일 ■정보관리학회지, 26(3): 261-278, 2009. [DOI:10.3743/KOSIM.2009.26.3.261] 262 정보관리학회지 제26권 제3호 2009