Toolboxes & Code Repositories

APS Explorer

A web application for exploring and selecting datasets based on informed criteria, designed to support recommender system experiments.

Description:


APS Explorer is a web application for exploring and selecting datasets based on informed criteria, designed to support recommender system experiments. It provides interactive visualizations and tools to compare algorithms and datasets using the Algorithm Performance Space (APS) framework.

More Information:

  • Related research challenge: AI-Driven Data Science

  • Responsible Research Lead: Bart Goethals

  • Authors: Tobias Vente, Michael Heep, Abdullah Abbas, Theodor Sperle, Joeran Beel, Bart Goethals

  • Link to the repository

  • Categories: Recommender systems

Publications:

  • Vente, T., Heep, M., Abbas, A., Sperle, T., Beel, J., & Goethals, B. (2025, September). APS Explorer: Navigating Algorithm Performance Spaces for Informed Dataset Selection. In Proceedings of the Nineteenth ACM Conference on Recommender Systems (pp. 1322-1324).