SimuRec

Workshop on synthetic data and simulation methods for recommender systems research

Conference paper (2021)

Authors

Michael D. Ekstrand Boise State University

Allison Chaney Duke University

Pablo Castells Campus de Cantoblanco

Robin Burke University of Colorado

David Rohde Criteo

M. Slokom

DOI: https://doi.org/10.1145/3460231.3470938

Simulation Evaluation Synthetic data

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Published Date

2021

Language

English

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Abstract

There is significant interest lately in using synthetic data and simulation infrastructures for various types of recommender systems research. However, there are not currently any clear best practices around how best to apply these methods. We proposed a workshop to bring together researchers and practitioners interested in simulating recommender systems and their data to discuss the state of the art of such research and the pressing open methodological questions. The workshop resulted in a report authored by the participants that documents currently-known best practices on which the group has consensus and lays out an agenda for further research over the next 3-5 years to fill in places where we currently lack the information needed to make methodological recommendations.

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