A Survey on Cross-Domain Sequential Recommendation

Chen, Shu; Xu, Zitao; Pan, Weike; Yang, Qiang; Ming, Zhong

doi:10.24963/ijcai.2024/884

A Survey on Cross-Domain Sequential Recommendation

Shu Chen, Zitao Xu, Weike Pan, Qiang Yang, Zhong Ming

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Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence. Survey Track. Pages 7989-7998.

https://doi.org/10.24963/ijcai.2024/884

Keywords

Data Mining: DM: Recommender systems

Abstract

Cross-domain sequential recommendation (CDSR) shifts the modeling of user preferences from flat to stereoscopic by integrating and learning interaction information from multiple domains at different granularities (ranging from inter-sequence to intra-sequence and from single-domain to cross-domain). In this survey, we initially define the CDSR problem using a four-dimensional tensor and then analyze its multi-type input representations under multidirectional dimensionality reductions. Following that, we provide a systematic overview from both macro and micro views. From a macro view, we abstract the multi-level fusion structures of various models across domains and discuss their bridges for fusion. From a micro view, focusing on the existing models, we specifically discuss the basic technologies and then explain the auxiliary learning technologies. Finally, we exhibit the available public datasets and the representative experimental results as well as provide some insights into future directions for research in CDSR.

Shu Chen, Zitao Xu, Weike Pan, Qiang Yang, and Zhong Ming. 2024. A Survey on Cross-Domain Sequential Recommendation. In Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI-24. IJCAI, 7989–7998. https://doi.org/10.24963/ijcai.2024/884

@inproceedings{ijcai2024p884,
  title     = {A Survey on Cross-Domain Sequential Recommendation},
  author    = {Chen, Shu and Xu, Zitao and Pan, Weike and Yang, Qiang and Ming, Zhong},
  booktitle = {Proceedings of the Thirty-Third International Joint Conference on
               Artificial Intelligence, {IJCAI-24}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Kate Larson},
  pages     = {7989--7998},
  year      = {2024},
  month     = {8},
  note      = {Survey Track},
  doi       = {10.24963/ijcai.2024/884},
  url       = {https://doi.org/10.24963/ijcai.2024/884},
}

TY  - CPAPER
TI  - A Survey on Cross-Domain Sequential Recommendation
AU  - Chen, Shu
AU  - Xu, Zitao
AU  - Pan, Weike
AU  - Yang, Qiang
AU  - Ming, Zhong
T2  - Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI-24
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2024
SP  - 7989
EP  - 7998
DO  - 10.24963/ijcai.2024/884
UR  - https://doi.org/10.24963/ijcai.2024/884
ER  -