On the Evaluation of Data Fusion for Information Retrieval
David Lillis
In Forum for Information Retrieval Evaluation (FIRE '20), Hyderabad, India, Dec. 2020.
Abstract
Data Fusion combines document rankings from multiple systems into one, in order to improve retrieval effectiveness. Many approaches to this task have been proposed in the literature, and these have been evaluated in various ways. This paper examines a number of such evaluations, to extract commonalities between approaches. Some drawbacks of the prevailing evaluation strategies are then identified, and suggestions made for more appropriate evaluation of data fusion.