Paper Info
Title
Disproving the fusion hypothesis: an analysis of data fusion via effective information retrieval strategies
Abstract
Many prior efforts have been devoted to the basic idea that data fusion techniques can improve retrieval effectiveness. Recent work in the area suggests that many approaches, particularly multiple-evidence combinations, can be a successful means of improving the effectiveness of a system. Unfortunately, the conditions favorable to effectiveness improvements have not been made clear. We examine popular data fusion techniques designed to achieve improvements in effectiveness and clarify the conditions required for data fusion to show improvement. We demonstrate that for fusion to improve effectiveness, the result sets being fused must contain a significant number of unique relevant documents. Furthermore, we show that for this improvement to be visible, these unique relevant documents must be highly ranked. In addition, we present a comprehensive discussion on why previous assumptions about the effectiveness of multiple-evidence techniques are misleading. Detailed empirical results and analysis are provided to support our conclusions.
Year
DOI
Venue
2003
10.1145/952532.952695
SAC
Keywords
Field
DocType
multiple-evidence technique,multiple-evidence combination,basic idea,data fusion,effectiveness improvement,comprehensive discussion,retrieval effectiveness,unique relevant document,fusion hypothesis,data fusion technique,effective information retrieval strategy,popular data fusion technique,information retrieval
Data analysis,Information retrieval,Ranking,Computer science,Fusion,Sensor fusion
Conference
ISBN
Citations 
PageRank 
1-58113-624-2
24
1.00
References 
Authors
15
6
Name
Order
Citations
PageRank
Steven M. Beitzel169646.72
Ophir Frieder23300419.55
Eric C. Jensen369646.72
David Grossman452534.73
Abdur Chowdhury52013160.59
Nazli Goharian646049.93