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Doklady Rossijskoj Akademii Nauk. Mathematika, Informatika, Processy Upravlenia, 2023, Volume 514, Number 2, Pages 333–342
DOI: https://doi.org/10.31857/S2686954323600428
(Mi danma477)
 

This article is cited in 1 scientific paper (total in 1 paper)

SPECIAL ISSUE: ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TECHNOLOGIES

MTS Kion implicit contextualised sequential dataset for movie recommendation

I. Safiloa, D. Tikhonovichb, A. V. Petrovc, D. I. Ignatovd

a MTS, HSE University, Moscow, Russian Federation
b MTS, Moscow, Russian Federation
c University of Glasgow, Glasgow, United Kingdom
d HSE University, Moscow, Russian Federation
Citations (1)
References:
Abstract: We present a new movie and TV show recommendation dataset collected from the real users of MTS Kion video-on-demand platform. In contrast to other popular movie recommendation datasets, such as MovieLens or Netflix, our dataset is based on the implicit interactions registered at the watching time, rather than on explicit ratings. We also provide rich contextual and side information including interactions characteristics (such as temporal information, watch duration and watch percentage), user demographics and rich movies meta-information. In addition, we describe the MTS Kion Challenge – an online recommender systems challenge that was based on this dataset – and provide an overview of the best performing solutions of the winners. We keep the competition sandbox open, so the researchers are welcome to try their own recommendation algorithms and measure the quality on the private part of the dataset.
Presented: A. I. Avetisyan
Received: 30.05.2023
Revised: 15.10.2023
Accepted: 20.10.2023
English version:
Doklady Mathematics, 2023, Volume 108, Issue suppl. 2, Pages S456–S464
DOI: https://doi.org/10.1134/S1064562423701594
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: I. Safilo, D. Tikhonovich, A. V. Petrov, D. I. Ignatov, “MTS Kion implicit contextualised sequential dataset for movie recommendation”, Dokl. RAN. Math. Inf. Proc. Upr., 514:2 (2023), 333–342; Dokl. Math., 108:suppl. 2 (2023), S456–S464
Citation in format AMSBIB
\Bibitem{SafTikPet23}
\by I.~Safilo, D.~Tikhonovich, A.~V.~Petrov, D.~I.~Ignatov
\paper MTS Kion implicit contextualised sequential dataset for movie recommendation
\jour Dokl. RAN. Math. Inf. Proc. Upr.
\yr 2023
\vol 514
\issue 2
\pages 333--342
\mathnet{http://mi.mathnet.ru/danma477}
\crossref{https://doi.org/10.31857/S2686954323600428}
\elib{https://elibrary.ru/item.asp?id=56717850}
\transl
\jour Dokl. Math.
\yr 2023
\vol 108
\issue suppl. 2
\pages S456--S464
\crossref{https://doi.org/10.1134/S1064562423701594}
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  • https://www.mathnet.ru/eng/danma/v514/i2/p333
  • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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    Doklady Rossijskoj Akademii Nauk. Mathematika, Informatika, Processy Upravlenia Doklady Rossijskoj Akademii Nauk. Mathematika, Informatika, Processy Upravlenia
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    References:9
     
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