Inquery and TREC-9
MASSACHUSETTS UNIV AMHERST CENTER FOR INTELLIGENT INFORMATION RETRIEVAL
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This year the Center for Intelligent Information Retrieval CIIR at the University of Massachusetts participated in three of the tracks the cross-language, question answering, and query tracks. We used approaches that were similar to those used in past years. Although UMass used a wide range of tools, from Unix shell scripts, to PC spreadsheets, three major tools and techniques were applied across almost all tracks the Inquery search engine, query processing, and a query expansion technique known as LCA. All three tracks used Inquery as the search engine, sometimes for training, and always for generating the final ranked lists for the test. In the cross language track, we experimented some techniques for crossing the character encoding boundaries. Our efforts were moderately successful, but we do not believe that our approach worked well in comparison to other techniques. In the question answering track, we focused on bringing answer-containing documents to the top of the ranked list. This is an important sub-task for most methods of tackling QA, and we are pleased with our results. We are now looking at alternate ways of thinking about that task that leverage the differences between retrieval for QA and for IR. Finally, we continued to participate in the query track, providing large numbers of query variants, and running our system on the huge number of resulting queries. Our analysis showed how query expansion compensates for some of the problems that can occurs in query formulation.
- Information Science
- Operations Research
- Computer Programming and Software