TTRS: Tinkoff transactions recommender system benchmark S Kolesnikov, O Lashinin, M Pechatov, A Kosov arXiv preprint arXiv:2110.05589, 2021 | 6 | 2021 |
Time-Dependent Next-Basket Recommendations S Naumov, M Ananyeva, O Lashinin, S Kolesnikov, DI Ignatov European Conference on Information Retrieval, 502-511, 2023 | 4 | 2023 |
Towards Interaction-based User Embeddings in Sequential Recommender Models. M Ananyeva, O Lashinin, V Ivanova, S Kolesnikov, DI Ignatov ORSUM@ RecSys, 2022 | 2 | 2022 |
RecBaselines2023: a new dataset for choosing baselines for recommender models V Ivanova, O Lashinin, M Ananyeva, S Kolesnikov arXiv preprint arXiv:2306.14292, 2023 | 1 | 2023 |
Make your next item recommendation model time sensitive E Makhneva, A Sverkunova, O Lashinin, M Ananyeva, S Kolesnikov Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation …, 2023 | 1 | 2023 |
Next-basket Recommendation Constrained by Total Cost. O Lashinin, M Ananyeva ORSUM@ RecSys, 2022 | 1 | 2022 |
Time-Aware Item Weighting for the Next Basket Recommendations A Romanov, O Lashinin, M Ananyeva, S Kolesnikov Proceedings of the 17th ACM Conference on Recommender Systems, 985-992, 2023 | | 2023 |
GPT3RecBot: a universal chatbot recommender of movies, books and music in Telegram O Lashinin, K Bykov, M Ananyeva, S Kolesnikov | | 2023 |
Utilising Crowdsourcing to Assess the Effectiveness of Item-based Explanations of Merchant Recommendations. D Krasilnikov, O Lashinin, M Tsygankov, M Ananyeva, S Kolesnikov CSW@ WSDM, 77-86, 2023 | | 2023 |
Pre-compiled Recommendation Lists for Online Recommendations D Krasilnikov, O Lashinin, M Ananyeva, S Kolesnikov | | 2022 |
Revisiting the performance evaluation of knowledge-aware recommender systems: are we making progress? M Ananyeva, O Lashinin, M Kuznetsova KaRS@ RecSys, 22-28, 2022 | | 2022 |
Next Period Recommendation Reality Check S Kolesnikov, O Lashinin, M Pechatov, A Kosov arXiv preprint arXiv:2110.05589, 2021 | | 2021 |