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SimuRec: Workshop on Synthetic Data and Simulation Methods for Recommender Systems Research
Conference proceeding   Open access

SimuRec: Workshop on Synthetic Data and Simulation Methods for Recommender Systems Research

Michael D. Ekstrand, Allison Chaney, Pablo Castells, Robin Burke, David Rohde, Manel Slokom and ACM
15TH ACM CONFERENCE ON RECOMMENDER SYSTEMS (RECSYS 2021), pp 803-805
01 Jan 2021
DOI: https://doi.org/10.1145/3460231.3470938
url
https://doi.org/10.1145/3460231.3470938View
Published, Version of Record (VoR)Open Access (License Unspecified),  Open

Abstract

evaluation synthetic data simulation
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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Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Computer Science, Artificial Intelligence
Computer Science, Information Systems
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