GCN-based Explainable Recommendation using a Knowledge Graph and a Language Model
Author:
Affiliation:
1. Sungkyunkwan University,Department of Industrial Engeneering,Suwon,South Korea
2. King’s College London,Department of Informatics,London,United Kingdom
Funder
Ministry of Education
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10385234/10386078/10386124.pdf?arnumber=10386124
Reference38 articles.
1. IA-GCN: Interactive Graph Convolutional Network for Recommendation;Zhang;arXiv preprint arXiv:2204.03827,2022
2. Neural Graph Collaborative Filtering
3. Solving cold-start problem in large-scale recommendation engines: A deep learning approach
4. KR-GCN: Knowledge-Aware Reasoning with Graph Convolution Network for Explainable Recommendation
5. Workflow for Domain- and Task-Sensitive Curation of Knowledge Graphs, with Use Case of DRKG
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