标题:Computing Concept Relatedness Based on Ontology
作者:Lu, Yanping; Hao, Xingwei; Tian, Shaocun
通讯作者:Lu, YP
作者机构:[Lu, Yanping; Hao, Xingwei; Tian, Shaocun] Shandong Univ, Sch Comp Sci & Technol, Jinan 250100, Peoples R China.
会议名称:8th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)
会议日期:NOV 20-23, 2013
来源:KNOWLEDGE ENGINEERING AND MANAGEMENT , ISKE 2013
出版年:2014
卷:278
页码:117-124
DOI:10.1007/978-3-642-54930-4_12
关键词:Domain ontology; Relevance; Similarity; Concept relatedness
摘要:Concept relatedness is widely used in information retrieval, text classification, semantic extension, and other fields. So measuring the concept relatedness efficiently is an important task. Previous studies rarely distinguish between relatedness and similarity; they usually use a common formula. We suggest that concept relatedness consists of similarity and relevance, which should be computed differently. In this paper, we first give a similarity measure based on path length, taxonomy depth, and different relations between concepts. Then we propose a method to measure the specific association relation besides basic relations. Finally, incorporating both similarity and specific relevance, we get an overall formula of computing concept relatedness. Compared to existing methods, our measure of concept relatedness is more consistent with human judgment.
收录类别:CPCI-S;EI;SCOPUS
Scopus被引频次:1
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903528795&doi=10.1007%2f978-3-642-54930-4_12&partnerID=40&md5=691201a23bb79397036aa5b66976ceda
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