Dataset selection shapes the empirical conditions under which recommender-system algorithms are evaluated, yet existing tools provide limited support for constructing complete dataset sets that jointly satisfy experimental constraints and set-level selection objectives. To address this problem, I developed FINALLY, a w...
FINALLY is a web-based recommender system for dataset selection in RecSys experiments. It supports a decision often made manually or by convention: choosing datasets to evaluate a recommendation algorithm offline. With FINALLY, users choose seed datasets, filters, a target set size, and a recommendation strategy. FINAL...
L. Owie, Tobias Vente, Joeran Beel· Proceedings of the 20th ACM...· 0 citations
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