Paper Info
Title
The linear combination data fusion method in information retrieval
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.
Year
DOI
Venue
2011
10.1007/978-3-642-23091-2_20
DEXA (2)
Keywords
Field
DocType
linear combination,best component system,data fusion,linear combination method,information retrieval,component retrieval system,linear combination data fusion,effective data fusion method,better fusion result,different component system,multiple linear regression technique,involved component system
Least squares,Linear combination,Data mining,Weighting,Open problem,Computer science,Fusion,Artificial intelligence,Linear regression,Component retrieval,Information retrieval,Pattern recognition,Sensor fusion
Conference
Citations 
PageRank 
References 
3
0.46
29
Authors
3
Name
Order
Citations
PageRank
Shengli Wu137033.55
Yaxin Bi254147.76
Xiaoqin Zeng340732.97