| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 387243 | Expert Systems with Applications | 2009 | 7 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Lixin Han, Guihai Chen,
