HQE: A hybrid method for query expansion

被引:9
|
作者
Han, Lixin [1 ,2 ,3 ]
Chen, Guihai [2 ]
机构
[1] Hohai Univ, Coll Comp & Informat Engn, Nanjing 210098, Jiangsu, Peoples R China
[2] Nanjing Univ, State Key Lab Novel Software Technol, Nanjing 210008, Peoples R China
[3] Nanjing Univ, Dept Math, Nanjing 210008, Peoples R China
基金
中国国家自然科学基金;
关键词
Information retrieval; Collaborative filtering; Data mining; Optimization; RETRIEVAL;
D O I
10.1016/j.eswa.2008.10.060
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Query expansion methods have been extensively studied in information retrieval. This paper proposes a query expansion method. The HQE method employs a combination of ontology-based collaborative filtering and neural networks to improve query expansion. In the HQE method, ontology-based collaborative filtering is used to analyze semantic relationships in order to find the similar users, and the radial basis function (RBF) networks are used to acquire the most relevant web documents and their corresponding terms from these similar users' queries. The method can improve the precision and only requires users to provide less query information at the beginning than traditional collaborative filtering methods. (c) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:7985 / 7991
页数:7
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