Mining dependency relations for query expansion in passage retrieval

Classical query expansion techniques such as the local context analysis (LCA) make use of term co-occurrence statistics to incorporate additional contextual terms for enhancing passage retrieval. However, relevant contextual terms do not always cooccur frequently with the query terms and vice versa. Hence the use of such methods often brings in noise, which leads to reduced precision. Previous studies have demonstrated the importance of relationship analysis for natural language queries in passage retrieval. However, they found that without query expansion, the performance is not satisfactory for short queries. In this paper, we present two novel query expansion techniques that make use of dependency relation analysis to extract contextual terms and relations from external corpuses. The techniques are used to enhance the performance of density based and relation based passage retrieval frameworks respectively. We compare the performance of the resulting systems with LCA in a density b...

• Type: Conference
• Year: 2006
• Where: SIGIR
• Authors: Renxu Sun, Chai-Huat Ong, Tat-Seng Chua
• Keywords: Passage Retrieval, Query Expansion, Query Expansion Techniques, SIGIR 2006