Incremental Learning for Multi-Interest Sequential Recommendation
Author:
Affiliation:
1. Shanghai Jiao Tong University,Department of Computer Science and Engineering,Shanghai,China
Funder
National Key Research and Development Program of China
Tencent
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10184508/10184509/10184671.pdf?arnumber=10184671
Reference41 articles.
1. Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems
2. Continual lifelong learning with neural networks: A review
3. How to Retrain Recommender System? A Sequential Meta-Learning Method;huang;Proceedings of ACM SIGIR International Conference on Research and Development in Information Retrieval,2020
4. Fusing Similarity Models with Markov Chains for Sparse Sequential Recommendation
5. Progressive Neural Networks;rusu;ArXiv,2016
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