Introduction to the Special Issue on Perspectives on Recommender Systems Evaluation

Christine Bauer*, Alan Said, Eva Zangerle

*Corresponding author for this work

Research output: Contribution to journalEditorial

Abstract

Evaluation plays a vital role in recommender systems—in research and practice—whether for confirming algorithmic concepts or assessing the operational validity of designs and applications. It may span the evaluation of early ideas and approaches up to elaborate implementations of systems integrated into everyday product settings; it may target a wide spectrum of different factors being evaluated. In this special issue, we explore recommender systems evaluation—theory and practice—while considering a diverse set of perspectives. These include recommender systems purposes, stakeholders, methodological approaches, and consequences. The collection of articles in this special issue offers insightful analyses of current recommender system evaluation practices, acknowledging their limitations, and setting out future research directions. As recommender systems evolve, the need for adequate evaluation methods and approaches increases. This special issue sheds light on areas undergoing development or requiring added attention from the research and practitioner communities in recommender systems. The compilation serves as a call to the recommender systems research community, motivating continued research and exploration of evaluation metrics, methods, and strategies.
Original languageEnglish
Article number1
Number of pages5
JournalACM Transactions on Recommender Systems
Volume2
Issue number1
DOIs
Publication statusPublished - 7 Mar 2024

Keywords

  • evaluation
  • recommender systems
  • reproducibility
  • datasets
  • metrics

Fields of Science and Technology Classification 2012

  • 102 Computer Sciences

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