Business information query expansion through semantic network

Gong, Zhiguo; Muyeba, Maybin; Guo, Jingzhi

Abstract

In this article, we propose a method for business information query expansions. In our approach, hypernym/hyponymy and synonym relations in WordNet are used as the basic expansion rules. Then we use WordNet Lexical Chains and WordNet semantic similarity to assign terms in the same query into different groups with respect to their semantic similarities. For each group, we expand the highest terms in the WordNet hierarchies with hypernym and synonym, the lowest terms with hyponym and synonym and all other terms with only synonym. In this way, the contradictory caused by full expansion can be well controlled. Furthermore, we use collection-related term semantic network to further improve the expansion performance. And our experiment reveals that our solution for query expansion can improve the query performance dramatically.

• Journal Article Type: Article
• Acceptance Date: Nov 21, 2009
• Online Publication Date: Jan 21, 2010
• Publication Date: 2010-02
• Deposit Date: Oct 4, 2024
• Journal: Enterprise Information Systems
• Print ISSN: 1751-7575
• Electronic ISSN: 1751-7583
• Publisher: Taylor and Francis
• Peer Reviewed: Peer Reviewed
• Volume: 4
• Issue: 1
• Pages: 1-22
• DOI: https://doi.org/10.1080/17517570903502856
• Keywords: e-business, business intelligence, business information, Web, query expansion, WordNet, term co-occurrence, search engine