An Experimental Study on Opinion Classification Using Supervised Latent Semantic Indexing(LSI) (지도적 잠재의미색인(LSI)기법을 이용한 의견 문서 자동 분류에 관한 실험적 연구)

Ji-Hye Lee (이지혜); Young-Mee Chung (정영미)

doi:10.3743/KOSIM.2009.26.3.451

An Experimental Study on Opinion Classification Using Supervised Latent Semantic Indexing(LSI)

Journal of the Korean Society for Information Management
Abbr : JKOSIM
2009, 26(3), pp.451~462
DOI : 10.3743/KOSIM.2009.26.3.451
Publisher : 한국정보관리학회
Research Area : Interdisciplinary Studies > Library and Information Science
Received : August 18, 2009
Accepted : September 3, 2009
Published : September 30, 2009

Ji-Hye Lee ¹, Young-Mee Chung ¹

¹연세대학교

Accredited

ABSTRACT

The aim of this study is to apply latent semantic indexing(LSI) techniques for efficient automatic classification of opinionated documents. For the experiments, we collected 1,000 opinionated documents such as reviews and news, with 500 among them labelled as positive documents and the remaining 500 as negative. In this study, sets of content words and sentiment words were extracted using a POS tagger in order to identify the optimal feature set in opinion classification. Findings addressed that it was more effective to employ LSI techniques than using a term indexing method in sentiment classification. The best performance was achieved by a supervised LSI technique.

KEYWORDS

opinion mining, sentiment classification, LSI, supervised latent semantic indexing, latent semantic indexing, term indexing

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Journal of the Korean Society for Information Management 2023 KCI Impact Factor : 1.31

An Experimental Study on Opinion Classification Using Supervised Latent Semantic Indexing(LSI)

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Citation status

* References for papers published after 2023 are currently being built.

Journal of the Korean Society for Information Management 2023 KCI Impact Factor : 1.31

An Experimental Study on Opinion Classification Using Supervised Latent Semantic Indexing(LSI)

ABSTRACT

KEYWORDS

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* References for papers published after 2023 are currently being built.