Towards stochastic simulations of relevance profiles
Kevin Roitero (Università degli Studi di Udine)
Andrea Brunello (Università degli Studi di Udine)
Julián Urbano (TU Delft - Multimedia Computing)
Stefano Mizzaro (Università degli Studi di Udine)
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Abstract
Recently proposed methods allow the generation of simulated scores representing the values of an effectiveness metric, but they do not investigate the generation of the actual lists of retrieved documents. In this paper we address this limitation: we present an approach that exploits an evolutionary algorithm and, given a metric score, creates a simulated relevance profile (i.e., a ranked list of relevance values) that produces that score. We show how the simulated relevance profiles are realistic under various analyses.