Multi-Domain Recommender Systems
5 papers with code • 0 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Multi-Domain Recommender Systems
RL-ISN-dataset
X-Wines
Latest papers
Exploiting Graph Structured Cross-Domain Representation for Multi-Domain Recommendation
alarca94/magrec
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This approach helps to mitigate the negative knowledge transfer problem from multiple domains and improve overall representation.
One for All, All for One: Learning and Transferring User Embeddings for Cross-Domain Recommendation
chain123/cat-art
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CAT-ART boosts the recommendation performance in any target domain through the combined use of the learned global user representation and knowledge transferred from other domains, in addition to the original user embedding in the target domain.
Decentralized Multi-Target Cross-Domain Recommendation for Multi-Organization Collaborations
Recommender Systems (RSs) are operated locally by different organizations in many realistic scenarios.
Dive into Deep Learning
d2l-ai/d2l-en
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This open-source book represents our attempt to make deep learning approachable, teaching readers the concepts, the context, and the code.
Microsoft Recommenders: Tools to Accelerate Developing Recommender Systems
The purpose of this work is to highlight the content of the Microsoft Recommenders repository and show how it can be used to reduce the time involved in developing recommender systems.
