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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Christensen, H.U., Ortiz-Arroyo, D. (2007). Applying Data Fusion Methods to Passage Retrieval in QAS. In: Haindl, M., Kittler, J., Roli, F. (eds) Multiple Classifier Systems. MCS 2007. Lecture Notes in Computer Science, vol 4472. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72523-7_9
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DOI: https://doi.org/10.1007/978-3-540-72523-7_9
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