Jan 10, 2022 · In this paper, we propose an end-to-end convolution and fusion model for cross-platform recommendation (CFCR).

The proposed CFCR model utilizes Graph Convolution Networks (GCN) to extract user and item features on graphs from different platforms, and fuses cross-platform ...

The proposed CFCR model utilizes Graph Convolution Networks (GCN) to extract user and item features on graphs from different platforms, ...

Shengze Yu's 4 research works with 8 citations, including: CFCR: A Convolution and Fusion Model for Cross-platform Recommendation.

CFCR: A Convolution and Fusion Model for Cross-platform Recommendation. ... Cross-platform Association for Cross-platform Video Recommendation. IJCAI 2019 ...

Cross-platform recommendation aims to improve recommendation accuracy through associating information from different platforms. Existing cross-platform ...

Readers: Everyone. CFCR: A Convolution and Fusion Model for Cross-platform Recommendation · pdf icon · hmtl icon · Shengze Yu, Xin Wang, Wenwu Zhu. Published: ...

In this paper, we propose an end-to-end convolution and fusion model for cross-platform recommendation (CFCR). The proposed CFCR model utilizes Graph ...

CFCR: A Convolution and Fusion Model for Cross-platform Recommendation. 5 minutes break for transition from Zoom to Gather.Town. 16:50 - 17:50 p.m., 18:50 - 19 ...

A transfer learning algorithm, named TLRec, for cross-domain recommendation, which exploits the overlapped users and items as a bridge to link different ...