Abstract
In this study, we performed a comprehensive evaluation of pseudo-relevance feedback technique for automatic query expansion using OHSUMED test collection. The well-known term sorting methods for the selection of expansion terms were tested in our experiments. We also proposed a new term reweighting method for further performance improvements. Through the multiple sets of test, we suggested that local context analysis was probably the most effective method of selecting good expansion terms from a set of MEDLINE documents given enough feedback documents. Both term sorting and term reweighting method might need to be carefully considered to achieve maximum performance improvements.
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Yoo, S., Choi, J. (2007). Improving MEDLINE Document Retrieval Using Automatic Query Expansion. In: Goh, D.HL., Cao, T.H., Sølvberg, I.T., Rasmussen, E. (eds) Asian Digital Libraries. Looking Back 10 Years and Forging New Frontiers. ICADL 2007. Lecture Notes in Computer Science, vol 4822. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77094-7_33
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DOI: https://doi.org/10.1007/978-3-540-77094-7_33
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