Live Session
Friday Posters
Demo
Introducing LensKit-Auto, an Experimental Automated Recommender System (AutoRecSys) Toolkit
Tobias Vente (University of Siegen), Michael Ekstrand (Boise State University) and Joeran Beel (University of Siegen).
Abstract
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 65.5% (19 out of 29) 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.