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Adaptive data fusion methods in information retrieval

Wu, S, Li, J, Zeng, X and Bi, Y (2014) Adaptive data fusion methods in information retrieval. Journal of the Association for Information Science and Technology, 65 (10). pp. 2048-2061. [Journal article]

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URL: http://onlinelibrary.wiley.com/doi/10.1002/asi.23140/abstract

DOI: 10.1002/asi.23140

Abstract

Data fusion is currently used extensively in information retrievalfor various tasks. It has proved to be a useful technology because it is able to improve retrieval performance frequently. However, in almost all prior research in data fusion, static search environments have been used, and dynamic search environments have generally not been considered.In this paper, we investigate adaptive data fusion methods that can changetheir behavior when the search environment changes.Three adaptive data fusion methods are proposed and investigated.In order to test these proposed methods properly, we generate a benchmark from ahistorical TREC data set. Experiments with the benchmark show that two of theproposed methods are good and may potentially be used in practice.

Item Type:Journal article
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:30819
Deposited By: Dr Shengli Wu
Deposited On:20 Jan 2015 16:36
Last Modified:20 Jan 2015 16:36

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