FairRecKit: A Web-based analysis software for recommender evaluations

Christine Bauer*, Lennard Chung, Aleksej Cornelissen, Isabelle van Driessel, Diede van der Hoorn, Yme de Jong, Lan Le, Sanaz Najiyan Tabriz, Roderick Spaans, Casper Thijsen, Robert Verbeeten, Vos Wesseling, Fern Wieland

*Corresponding author for this work

Research output: Contribution to conferencePaperAcademic


FairRecKit is a web-based analysis software that supports researchers in performing, analyzing, and understanding recommendation computations. The idea behind FairRecKit is to facilitate the in-depth analysis of recommendation outcomes considering fairness aspects. With (nested) filters on user or item attributes, metrics can easily be compared across user and item subgroups. Further, (nested) filters can be used on the dataset level; this way, recommendation outcomes can be compared across several sub-datasets to analyze for differences considering fairness aspects. The software currently features five datasets, 11 metrics, and 21 recommendation algorithms to be used in computational experimentation. It is open source and developed in a modular manner to facilitate extension. The analysis software consists of two components: A software package (FairRecKitLib) for running recommendation algorithms on the available datasets and a web-based user interface (FairRecKitApp) to start experiments, retrieve results of previous experiments, and analyze details. The application also comes with extensive documentation and options for result customization, which makes for a flexible tool that supports in-depth analysis.
Original languageEnglish
Number of pages6
Publication statusPublished - 19 Mar 2023
Event8th ACM SIGIR Conference on Human Information Interaction and Retrieval - Austin, United States
Duration: 19 Mar 202323 Mar 2023
Conference number: 8


Conference8th ACM SIGIR Conference on Human Information Interaction and Retrieval
Abbreviated titleCHIIR 2023
Country/TerritoryUnited States
Internet address


  • FairRecKit
  • resource
  • toolkit
  • analysis software
  • web-based evaluation
  • analysis
  • recommender systems
  • music
  • movies
  • evaluation
  • web-based


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