CATN: Cross-Domain Recommendation for Cold-Start Users via Aspect Transfer Network

@article{Zhao2020CATNCR,
  title={CATN: Cross-Domain Recommendation for Cold-Start Users via Aspect Transfer Network},
  author={Cheng Zhao and Chenliang Li and Rong Xiao and H. Deng and Aixin Sun},
  journal={Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval},
  year={2020}
}
  • Cheng Zhao, Chenliang Li, +2 authors Aixin Sun
  • Published 2020
  • Computer Science
  • Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval
  • In a large recommender system, the products (or items) could be in many different categories or domains. Given two relevant domains (e.g., Book and Movie), users may have interactions with items in one domain but not in the other domain. To the latter, these users are considered as cold-start users. How to effectively transfer users' preferences based on their interactions from one domain to the other relevant domain, is the key issue in cross-domain recommendation. Inspired by the advances… CONTINUE READING

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