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Personalized Document Snippet Extraction Method using Fuzzy Association and Pseudo Relevance Feedback  

Park, Seon (Institute Research of Information Science and Engineering, Mokpo National University)
Jo, Gwang-Mun (Department of Electronic Commerce, Mokpo National University)
Yang, Hu-Yeol (Department of Electronic Commerce, Mokpo National University)
Lee, Seong-Ro (Department of Information Electronic Engineering, Mokpo National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.49, no.2, 2012 , pp. 137-142 More about this Journal
Abstract
Snippet is a summaries information of representing web pages which search engine provides user. Snippet and page rank in search engine abundantly influence user for visiting web pages. User sometime visits the wrong page with respect to user intention when uses snippet. The snippet extraction method is difficult to accurate comprehending user intention. In order to solve above problem, this paper proposes a new snippet extraction method using fuzzy association and pseudo relevance feedback. The proposed method uses pseudo relevance feedback to expand the use's query. It uses the fuzzy association between the expanded query and the web pages to extract snippet to be well reflected semantic user's intention. The experimental results demonstrate that the proposed method can achieve better snippet extraction performance than the other methods.
Keywords
snippet; pseudo relevance feedback; fuzzy association; personalized document;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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