文章基本信息

标题：Re-Ranking Retrieval Model Based on Two-Level Similarity Relation Matrices
本地全文：下载
作者：Hee-Ju Eun
期刊名称：International Journal of Software Engineering and Its Applications
印刷版ISSN：1738-9984
出版年度：2015
卷号：9
期号：12
页码：349-360
DOI：10.14257/ijseia.2015.9.12.31
出版社：SERSC
摘要：Web-based specialized retrieval systems for scientific fields extremely restrict the expression for user's information requests. Therefore the process of information content analysis and that of the information acquisition become inconsistent. In this paper, we apply the fuzzy retrieval model to solve the high time complexity of the retrieval system by constructing a reduced term set for the term's relatively important degree. We also perform a cluster retrieval to reflect the user's query exactly through the similarity relation matrix satisfying the characteristics of the fuzzy compatibility relation. This paper proves the performance of a proposed re-ranking model based on the union of similarity of the fuzzy retrieval model and the document cluster retrieval model.
关键词：Similarity Relation Matrix; Time Complexity; Concept Information; Cluster; ; Thesaurus; Membership function; Reduction Term; Re-ranking Retrieval Model