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  • 한국과학기술정보연구원(KISTI) 서울분원 대회의실(별관 3층)
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  • P-ISSN1013-0799
  • E-ISSN2586-2073
  • KCI

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Vol.26 No.2

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딜리셔스에서 유사태그 추출에 관한 연구

Mining Semantically Similar Tags from Delicious

정보관리학회지 / Journal of the Korean Society for Information Management, (P)1013-0799; (E)2586-2073
2009, v.26 no.2, pp.127-147
https://doi.org/10.3743/KOSIM.2009.26.2.127
이관 (Univ. of Kentucky)
이관. (2009). 딜리셔스에서 유사태그 추출에 관한 연구. 정보관리학회지, 26(2), 127-147, https://doi.org/10.3743/KOSIM.2009.26.2.127

Abstract

The synonym issue is an inherent barrier in human-computer communication, and it is more challenging in a Web 2.0 application, especially in social tagging applications. In an effort to resolve the issue, the goal of this study is to test the feasibility of a Web 2.0 application as a potential source for synonyms. This study investigates a way of identifying similar tags from a popular collaborative tagging application, Delicious. Specifically, we propose an algorithm (FolkSim) for measuring the similarity of social tags from Delicious. We compared FolkSim to a cosine-based similarity method and observed that the top-ranked tags on the similar list generated by FolkSim tend to be among the best possible similar tags in given choices. Also, the lists appear to be relatively better than the ones created by CosSim. We also observed that tag folksonomy and similar list resemble each other to a certain degree so that it possibly serves as an alternative outcome, especially in case the FolkSim-based list is unavailable or infeasible.

keywords
유사태그, 딜리셔스, 유사어 추출, 폭소노미, 웹 마이닝, tag similarity, Delicious, synonym extraction, Folksonomy, web mining, tag similarity, Delicious, synonym extraction, Folksonomy, web mining

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