Abstract
In this paper we present FuzzyPR, a novel fuzzy logic based passage retrieval system for Question Answering Systems (QAS). FuzzyPR employs a fuzzy logic based similarity measure that includes the best performing models to implement the question reformulation intuition. Our experiments show that FuzzyPR achieves consistently better performance in terms of coverage than JIRS on the TREC corpora and slightly better on the CLEF corpora. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Christensen, H. U., & Ortiz-Arroyo, D. (2007). FuzzyPR: An effective passage retrieval system for QAS. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4482 LNAI, pp. 199–207). Springer Verlag. https://doi.org/10.1007/978-3-540-72530-5_23
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