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arXiv · 2208.12356

Lib-SibGMU -- A University Library Circulation Dataset for Recommender Systems Developmen

Eduard Zubchuk·Mikhail Arhipkin·Dmitry Menshikov·Aleksandr Karaush·Nikolay Mikhaylovskiy
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Abstract

We opensource under CC BY 4.0 license Lib-SibGMU - a university library circulation dataset - for a wide research community, and benchmark major algorithms for recommender systems on this dataset. For a recommender architecture that consists of a vectorizer that turns the history of the books borrowed into a vector, and a neighborhood-based recommender, trained separately, we show that using the fastText model as a vectorizer delivers competitive results.

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Eduard Zubchuk, Mikhail Arhipkin, Dmitry Menshikov, Aleksandr Karaush, Nikolay Mikhaylovskiy. 2022-08-25. Lib-SibGMU -- A University Library Circulation Dataset for Recommender Systems Developmen. https://arxiv.org/abs/2208.12356

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