Ulster University Logo

The Linear Combination Data Fusion Method in Information Retrieval

Wu, Shengli, Bi, Yaxin and zeng, xiaoqin (2011) The Linear Combination Data Fusion Method in Information Retrieval. In: DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II. Springer-Verlag Berlin. 14 pp. [Conference contribution]

Full text not available from this repository.

Abstract

In information retrieval, data fusion has been investigated by many researchers. Previous investigation and experimentation demonstrate that the linear combination method is an effective data fusion method for combining multiple information retrieval results. One advantage is its flexibility since different weights can be assigned to different component systems so as to obtain better fusion results. However, how to obtain suitable weights for all the component retrieval systems is still an open problem. In this paper, we use the multiple linear regression technique to obtain optimum weights for all involved component systems. Optimum is in the least squares sense that minimize the difference between the estimated scores of all documents by linear combination and the judged scores of those documents. Our experiments with four groups of runs submitted to TREC show that the linear combination method with such weights steadily outperforms the best component system and other major data fusion methods such as CombSum, CombMNZ, and the linear combination method with performance level/performance square weighting schemas by large margins.

Item Type:Conference contribution (Paper)
Keywords:Data Fusion, Information Retrieval, TREC
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:25458
Deposited By: Dr Yaxin Bi
Deposited On:20 Jan 2016 12:30
Last Modified:20 Jan 2016 12:30

Repository Staff Only: item control page