Towards stochastic simulations of relevance profiles

0Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.
Get full text

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.

Cite

CITATION STYLE

APA

Roitero, K., Brunello, A., Urbano, J., & Mizzaro, S. (2019). Towards stochastic simulations of relevance profiles. In International Conference on Information and Knowledge Management, Proceedings (pp. 2217–2220). Association for Computing Machinery. https://doi.org/10.1145/3357384.3358123

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free