Identifiability of Cross-Domain Recommendation via Causal Subspace Disentanglement
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- Identifiability of Cross-Domain Recommendation via Causal Subspace Disentanglement
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SIGIR '24: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information RetrievalThis paper explores Multi-Domain Sequential Recommendation (MDSR), an advancement of Multi-Domain Recommendation that incorporates sequential context. Recent MDSR approach exploits domain-specific sequences, decoupled from mixed-domain histories, to ...
C²DR: Robust Cross-Domain Recommendation based on Causal Disentanglement
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Cross-domain Recommendation via Adversarial Adaptation
CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge ManagementData scarcity, e.g., labeled data being either unavailable or too expensive, is a perpetual challenge of recommendation systems. Cross-domain recommendation leverages the label information in the source domain to facilitate the task in the target ...
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- General Chairs:
- Grace Hui Yang,
- Hongning Wang,
- Sam Han,
- Program Chairs:
- Claudia Hauff,
- Guido Zuccon,
- Yi Zhang
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Association for Computing Machinery
New York, NY, United States
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- Chinese Scholarship Council
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