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Aug 10, 2023 · We propose a new MDR method named EDDA with two key components, i.e., embedding disentangling recommender and domain alignment, to tackle the ...
We propose a new MDR method named EDDA with two key components, i.e., embedding disentangling recommender and domain alignment, to tackle the two challenges ...
EDDA [33] disentangles embeddings and aligns domains to enhance domain knowledge generalization and knowledge transfer across domains. MetaDomain [49] employs a ...
We propose a new MDR method named EDDA with two key components, i. e., embedding disentangling recommender and domain alignment, to tackle the two challenges ...
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May 24, 2024 · Multi-task learning (MTL) methods for Multi-Domain Recommendation (MDR) can be primarily categorized into single-embedding (SE) and multi- ...
Oct 21, 2024 · Learning high-quality item embeddings is crucial for recommendation tasks such as matching and ranking. However, existing methods often rely ...
An Automatic Domain Feature Extraction and Personalized Integration (DFEI) framework for the large-scale multi-domain recommendation that achieves ...
Nov 19, 2024 · Multi-domain Recommendation with Embedding Disentangling and Domain Alignment. CIKM'23. [2]. PLATE: A Prompt-Enhanced Paradigm for Multi- ...
Nov 20, 2024 · Multi-domain learning (MDL) has become a prominent topic in enhancing the quality of personalized services.
Multi-domain Recommendation with Embedding Disentangling and Domain Alignment. ... Multi-domain Recommendation with Embedding Disentangling and Domain Alignment.