Applying data fusion methods to passage retrieval in QAS
Abstract
This paper investigates the use of diverse data fusion methods to improve the performance of the passage retrieval component in a question answering system. Our results obtained with 13 data fusion methods and 8 passage retrieval systems show that data fusion techniques are capable of improving the performance of a passage retrieval system by 6.43% and 11.32% in terms of the mean reciprocal rank and coverage measures respectively.
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- Applying data fusion methods to passage retrieval in QAS
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- EU IST FP6 BioSecure Network of Excellence
- EU IST FP6 MUSCLE Network of Excellence
- IAPR: International Association for Pattern Recognition
- University of Surrey
- University of Cagliari: University of Cagliari
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Springer-Verlag
Berlin, Heidelberg
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Published: 23 May 2007
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