Applying data fusion methods to passage retrieval in QAS

Authors:
Hans Ulrich Christensen;Daniel Ortiz-Arroyo
Affiliations:
Computer Science Department, Aalborg University Esbjerg, Denmark;Computer Science Department, Aalborg University Esbjerg, Denmark
Venue:
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Year:
2007

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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.