Abstract
In data fusion, the linear combination method is a very flexible method since different weights can be assigned to different systems. When using the linear combination method, how to decide weights is a key issue. Profitable weights assignment is affected by a few factors mainly including performance of all component results and similarity among component results. In this chapter, we are going to discuss a few different methods for weights assignment. Extensive experimental results with TREC data are given to evaluate the effectiveness of these weights assignment methods and to reveal the properties of the linear combination data fusion methods.
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© 2012 Springer-Verlag Berlin Heidelberg
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Wu, S. (2012). The Linear Combination Method. In: Data Fusion in Information Retrieval. Adaptation, Learning, and Optimization, vol 13. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28866-1_5
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DOI: https://doi.org/10.1007/978-3-642-28866-1_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28865-4
Online ISBN: 978-3-642-28866-1
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