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An Opinionated Document Retrieval System based on Hybrid Method

  • Journal of the Korean Society for Information Management
  • Abbr : JKOSIM
  • 2008, 25(4), pp.115~129
  • DOI : 10.3743/KOSIM.2008.25.4.115
  • Publisher : 한국정보관리학회
  • Research Area : Interdisciplinary Studies > Library and Information Science
  • Received : November 13, 2008
  • Accepted : November 26, 2008
  • Published : December 30, 2008

Seung-Wook Lee 1 Young-In Song 1 Hae-Chang Rim 2

1고려대학교 정보통신대학원
2고려대학교

Accredited

ABSTRACT

Recently, as its growth and popularization, the Web is changed into the place where people express, share and debate their opinions rather than the space of information seeking. Accordingly, the needs for searching opinions expressed in the Web are also increasing. However, it is difficult to meet these needs by using a classical information retrieval system that only concerns the relevance between the user's query and documents. Instead, a more advanced system that captures subjective information through documents is required. The proposed system effectively retrieves opinionated documents by utilizing an existing information retrieval system. This paper proposes a kind of hybrid method which can utilize both a dictionary-based opinion analysis technique and a machine learning based opinion analysis technique. Experimental results show that the proposed method is effective in improving the performance.

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