Enhancing the Performance of Blog Retrieval by User Tagging and Social Network Analysis (사용자 태그와 중심성 지수를 이용한 블로그 검색 성능 향상에 관한 연구)

Eun-Hee Kim (김은희); Young-Mee Chung (정영미)

doi:10.3743/KOSIM.2010.27.1.061

Enhancing the Performance of Blog Retrieval by User Tagging and Social Network Analysis

Journal of the Korean Society for Information Management
Abbr : JKOSIM
2010, 27(1), pp.61~77
DOI : 10.3743/KOSIM.2010.27.1.061
Publisher : 한국정보관리학회
Research Area : Interdisciplinary Studies > Library and Information Science
Received : February 1, 2010
Accepted : March 10, 2010
Published : March 30, 2010

Eun-Hee Kim ¹, Young-Mee Chung ¹

¹연세대학교

Accredited

ABSTRACT

Blogs are now one of the major information resources on the web. The purpose of this study is to enhance the performance of blog retrieval by means of user assigned tags and trackback information. To this end, retrieval experiments were performed with a dataset of 4,908 blog pages together with their associated trackback URLs. In the experiments, text terms, user tags, and network centrality values based on trackbacks were variously combined as retrieval features. The experimental results showed that employing user tags and network centrality values as retrieval features in addition to text words could improve the performance of blog retrieval.

KEYWORDS

blog retrieval, user tags, trackbacks, network centrality, social network analysis

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

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

Enhancing the Performance of Blog Retrieval by User Tagging and Social Network Analysis

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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

Enhancing the Performance of Blog Retrieval by User Tagging and Social Network Analysis

ABSTRACT

KEYWORDS

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KCI Citation Counts (7)

REFERENCES (33) * References for papers published after 2023 are currently being built.

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