Multi-modal Graph Contrastive Learning for Micro-video Recommendation-Reference-Cited by-同舟云学术

Multi-modal Graph Contrastive Learning for Micro-video Recommendation

Published:2022-07-06 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
language:
Short-container-title:

Author:

Yi Zixuan¹,Wang Xi¹,Ounis Iadh¹,Macdonald Craig¹

Affiliation:

1. University of Glasgow, Glasgow, United Kingdom

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3477495.3532027

Reference26 articles.

1. Context-aware Image Tweet Modelling and Recommendation

2. Ting Chen , Simon Kornblith , Mohammad Norouzi , and Geoffrey Hinton . 2020 . A simple framework for contrastive learning of visual representations . In Proceedings of the 37th International Conference on Machine Learning. PMLR, 1597--1607 . Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton. 2020. A simple framework for contrastive learning of visual representations. In Proceedings of the 37th International Conference on Machine Learning. PMLR, 1597--1607.

3. How to Learn Item Representation for Cold-Start Multimedia Recommendation?

4. A Unified Personalized Video Recommendation via Dynamic Recurrent Neural Networks

5. Structured Multi-modal Feature Embedding and Alignment for Image-Sentence Retrieval

Cited by 41 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multimodal Recommender Systems: A Survey;ACM Computing Surveys;2024-09-10

2. Multimodal deep hierarchical semantic-aligned matrix factorization method for micro-video multi-label classification;Information Processing & Management;2024-09

3. Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

4. M3KGR: A momentum contrastive multi-modal knowledge graph learning framework for recommendation;Information Sciences;2024-08

5. Multi-level cross-modal contrastive learning for review-aware recommendation;Expert Systems with Applications;2024-08