17 citations · 27 across the 5 of their papers we have counts for
5 papers
SAFERec: Self-Attention and Frequency Enriched Model for Next Basket Recommendation
Oleg Lashinin, Denis Krasilnikov, Aleksandr Milogradskii +1
Transformer-based approaches such as BERT4Rec and SASRec demonstrate strong performance in Next Item Recommendation (NIR) tasks. However, applying these architectures to Next-Baske…
Revisiting BPR: A Replicability Study of a Common Recommender System Baseline
Aleksandr Milogradskii, Oleg Lashinin, Alexander P +2
Bayesian Personalized Ranking (BPR), a collaborative filtering approach based on matrix factorization, frequently serves as a benchmark for recommender systems research. However, n…
Time-Aware Item Weighting for the Next Basket Recommendations
Aleksey Romanov, Oleg Lashinin, Marina Ananyeva +1
In this paper we study the next basket recommendation problem. Recent methods use different approaches to achieve better performance. However, many of them do not use information a…
RecBaselines2023: a new dataset for choosing baselines for recommender models
Veronika Ivanova, Oleg Lashinin, Marina Ananyeva +1
The number of proposed recommender algorithms continues to grow. The authors propose new approaches and compare them with existing models, called baselines. Due to the large number…
Next Period Recommendation Reality Check
Sergey Kolesnikov, Oleg Lashinin, Michail Pechatov +1
Over the past decade, tremendous progress has been made in Recommender Systems (RecSys) for well-known tasks such as next-item and next-basket prediction. On the other hand, the re…