Aleksandr V. Petrov

According to our database, Aleksandr V. Petrov authored at least 19 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

GLoSS: Generative Language Models with Semantic Search for Sequential Recommendation.

Krishna Acharya, Aleksandr V. Petrov, Juba Ziani

CoRR, June, 2025

RSS: Effective and Efficient Training for Sequential Recommendation Using Recency Sampling.

Aleksandr V. Petrov, Craig Macdonald

Trans. Recomm. Syst., March, 2025

Efficient Recommendation with Millions of Items by Dynamic Pruning of Sub-Item Embeddings.

Aleksandr V. Petrov, Craig Macdonald, Nicola Tonellotto

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

CountNet: Utilising Repetition Counts in Sequential Recommendation.

Aleksandr V. Petrov, Efi Karra Taniskidou, Sean Murphy

Proceedings of the Advances in Information Retrieval, 2025

Improving Minimax Group Fairness in Sequential Recommendation.

Krishna Acharya, David Wardrope, Timos Korres, Aleksandr V. Petrov, Anders Uhrenholt

Proceedings of the Advances in Information Retrieval, 2025

2024

Aligning GPTRec with Beyond-Accuracy Goals with Reinforcement Learning.

Aleksandr V. Petrov, Craig Macdonald

CoRR, 2024

RecJPQ: Training Large-Catalogue Sequential Recommenders.

Aleksandr V. Petrov, Craig Macdonald

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Efficient Inference of Sub-Item Id-based Sequential Recommendation Models with Millions of Items.

Aleksandr Vladimirovich Petrov, Craig Macdonald, Nicola Tonellotto

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

Enhancing Sequential Music Recommendation with Personalized Popularity Awareness.

Davide Abbattista, Vito Walter Anelli, Tommaso Di Noia, Craig MacDonald, Aleksandr Vladimirovich Petrov

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling (Extended Abstract).

Aleksandr V. Petrov, Craig Macdonald

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Shallow Cross-Encoders for Low-Latency Retrieval.

Aleksandr V. Petrov, Sean MacAvaney, Craig Macdonald

Proceedings of the Advances in Information Retrieval, 2024

Transformers for Sequential Recommendation.

Aleksandr V. Petrov, Craig Macdonald

Proceedings of the Advances in Information Retrieval, 2024

Effective and Efficient Transformer Models for Sequential Recommendation.

Aleksandr V. Petrov

Proceedings of the Advances in Information Retrieval, 2024

2023

Generative Sequential Recommendation with GPTRec.

Aleksandr V. Petrov, Craig Macdonald

CoRR, 2023

gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling.

Aleksandr Vladimirovich Petrov, Craig MacDonald

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

2022

MTS Kion Implicit Contextualised Sequential Dataset for Movie Recommendation.

Aleksandr V. Petrov, Ildar Safilo, Daria Tikhonovich, Dmitry I. Ignatov

CoRR, 2022

A Systematic Review and Replicability Study of BERT4Rec for Sequential Recommendation.

Aleksandr V. Petrov, Craig Macdonald

Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

Effective and Efficient Training for Sequential Recommendation using Recency Sampling.

Aleksandr V. Petrov, Craig Macdonald

Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

2021

Attention-based neural re-ranking approach for next city in trip recommendations.

Aleksandr V. Petrov, Yuriy Makarov

Proceedings of the Workshop on Web Tourism co-located with the 14th ACM International WSDM Conference (WSDM 2021), 2021