Introducing LensKit-Auto, an Experimental Automated Recommender System (AutoRecSys) Toolkit

Tobias Vente, Michael D. Ekstrand,Joeran Beel

PROCEEDINGS OF THE 17TH ACM CONFERENCE ON RECOMMENDER SYSTEMS, RECSYS 2023(2023)

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摘要
LensKit is one of the first and most popular Recommender System libraries. While LensKit offers a wide variety of features, it does not include any optimization strategies or guidelines on how to select and tune LensKit algorithms. LensKit developers have to manually include third-party libraries into their experimental setup or implement optimization strategies by hand to optimize hyperparameters. We found that 63.6% (21 out of 33) of papers using LensKit algorithms for their experiments did not select algorithms or tune hyperparameters. Non-optimized models represent poor baselines and produce less meaningful research results. This demo introduces LensKit-Auto. LensKit-Auto automates the entire Recommender System pipeline and enables LensKit developers to automatically select, optimize, and ensemble LensKit algorithms.
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关键词
Recommender Systems,Automated Recommender Systems,AutoRecSys,Algorithm Selection,Hyperparameter Optimization,CASH
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