A novel framework is proposed to integrate KGE into the DLRS in recommender system. •. A CIS layer is designed to address the challenge of data sparsity and ...
A multitask recommendation algorithm based on DeepFM and Graph Convolutional Network ... For a long time, the problems of cold start and sparse data have always ...
Extensive experiments on several public datasets, as well as online AB tests of an industrial recommendation scenario in the Ant Financial Service Group, ...
This work proposes MDAR, a multi-task learning approach that combines DeepFM with an attention mechanism (DeepAFM) and a relation-fused multi-head graph ...
Jan 11, 2024 · Online news recommender systems aim to address the information explosion of news and make personalized recommendation for users.
Missing: DKEN: | Show results with:DKEN:
1, DKEN: Deep Knowledge-enhanced Network for Recommender Systems IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View
Oct 17, 2022 · A multi-view deep learning approach for cross domain user modeling in recommendation systems. In Proceedings of the 24th international ...
Missing: DKEN: | Show results with:DKEN:
Jun 29, 2020 · Despite that existing knowledge graphs embedding (KGE) based methods can achieve better recommendation performance compared with deep ...
In this section, we introduce the related literature about deep rec- ommendation system, generation of recommendation candidates, knowledge graph recommendation ...
To cope with this, we delve into the diversified RecSys un- der the knowledge graphs (KG) framework. Extensive literature has been published on recommender ...