This paper focuses on learning explicit mapping between a user's behaviors (ie interaction itemsets) in different domains during the same temporal period.

Cross-domain recommendation methods usually transfer knowledge across different domains im- plicitly, by sharing model parameters or learning parameter mappings ...

This paper proposes a novel deep cross-domain recommendation model, called Cycle Generation Networks (CGN), which employs two generators to construct the ...

Jan 7, 2021 · In this paper, we propose a novel deep cross-domain recommendation model, called Cycle Generation Networks (CGN). Specifically, CGN employs two ...

In this paper, we propose a novel deep cross-domain recommendation model, called Cycle Generation Networks (CGN). Specifically, CGN employs two generators to ...

In IEEE Transactions on Knowledge and Data Engineering. Regular paper. [Paper]. 2020. Learning Personalized Itemset Mapping for Cross-Domain Recommendation.

This repository contains several state-of-the-art models of recommender system created using the PyTorch framework. The training data used were taken from ...

Learning Personalized Itemset Mapping for Cross-Domain. Recommendation. In Proceedings of the Twenty-Ninth International Joint Confer- ence on Artificial ...

Learning Personalized Itemset Mapping for Cross-Domain Recommendation. Conference Paper. Jul 2020. Yinan Zhang · Yong Liu · Peng Han · Haihong Tang. Cross ...

Jan 22, 2024 · Our method introduces a two-step domain-aware cross-attention, extracting transferable features of the source domain from different granularity.