文献类型：期刊文献

英文题名：Fusion of user recommended web data for entity search

作者：Zhang, Naizhou[1]; Zhang, Yadong[1]; Cao, Wei[2]

第一作者：张乃洲

通讯作者：Zhang, N.|[1048458a2b4a39]张宁;

机构：[1] College of Computer and Information Engineering, Henan University of Economics and Law, Zhengzhou 450002, China; [2] Computer College, Wuhan Institute of Technology, Wuhan 430074, China

第一机构：河南财经政法大学计算机与信息工程学院

通讯机构：[1]College of Computer and Information Engineering, Henan University of Economics and Law, Zhengzhou 450002, China|[1048412]河南财经政法大学计算机与信息工程学院;[10484]河南财经政法大学;

年份：2012

卷号：8

期号：3

起止页码：957-964

外文期刊名：Journal of Computational Information Systems

收录：EI(收录号：20121314906721);Scopus(收录号：2-s2.0-84863341734)

语种：英文

外文关键词：Algorithms - Data fusion - Search engines - Semantic Web - Semantics

摘要：The traditional architecture of search engine has been faced with some challenges, such as limited resources, semantic understanding, accurate search, etc. While social data annotated by web users, through adding some accurate semantic information to them, can be exploited to solve these problems to some extent. In this paper, we investigate a number of key techniques integrating user social data recommendation into entity search engine. For the purpose of fusing structural information into entity search engine, we present formal definitions related to web entity fusion, and discuss several data fusion operators in detail. Finally, we propose the web entity fusion algorithm. Our experimental results show that the proposed algorithms are effective. 1553-9105/Copyright ? 2012 Binary Information Press.