WIDIT: integrated approach to HARD topic search

• Authors: Kiduk Yang;Ning Yu;Hui Zhang;Shahrier Akram;Ivan Record
• Venue: AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
• Year: 2006

Web Information Discovery Tool (WIDIT) Laboratory at the Indiana University School of Library, whose basic approach to combine multiple methods as well as to leverage multiple sources of evidence, participated in 2005 Text Retrieval Conference’s Hard track (HARD-2005) to investigate methods of effectively dealing with HARD topics by exploring a variety of query expansion strategies, the results of which were combined via an automatic fusion optimization process. We hypothesized that the “difficulty” of topics is often due to the lack of appropriate query terms and/or misguided emphasis on non-pivotal query terms by the system. Thus, our first-tier solution was to devise a wide range of query expansion methods that can not only enrich the query with useful term additions but also identify important query terms. Our automatic query expansion included such techniques as noun phrase extraction, synonym identification, definition term extraction, keyword extraction by overlapping sliding window, and Web query expansion. The results of automatic expansion were used in soliciting user feedback, which was utilized in a post-retrieval reranking process. The paper describes our participation in HARD-2005 and is organized as follows. Section 2 gives an overview of HARD track, section 3 describes the WIDIT approach to HARD-2005, and section 4 discusses the results and implications, followed by the concluding remarks in section 5.