Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation-Reference-Cited by-同舟云学术

Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation

Published:2024-03-04 Issue: Volume:17 Page:548-556
ISSN:
Container-title:Proceedings of the 17th ACM International Conference on Web Search and Data Mining
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Author:

Qin Xiuyuan¹^ORCID,Yuan Huanhuan¹^ORCID,Zhao Pengpeng¹^ORCID,Liu Guanfeng²^ORCID,Zhuang Fuzhen³^ORCID,Sheng Victor S.⁴^ORCID

Affiliation:

1. Soochow University, SuZhou, China

2. Macquarie University, Sydney, NSW, Australia

3. Institute of Artificial Intelligence & SKLSDE, School of Computer Science, Beihang University, Beijing, China

4. Texas Tech University, Lubbock, USA

Funder

NSFC

Suzhou Science and Technology Development Program

natural science research in Universities of Jiangsu Province

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3616855.3635773

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3. Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey E. Hinton. 2020a. A Simple Framework for Contrastive Learning of Visual Representations. In ICML. 1597--1607.

4. Wanyu Chen Pengjie Ren Fei Cai Fei Sun and Maarten de Rijke. 2020b. Improving End-to-End Sequential Recommendations with Intent-aware Diversification. In CIKM. 175--184.

5. Yongjun Chen Zhiwei Liu Jia Li Julian J. McAuley and Caiming Xiong. 2022. Intent Contrastive Learning for Sequential Recommendation. In WWW. 2172--2182.