Simple and Efficient Knowledge Graph Attention Network for Recommendation-Reference-Cited by-同舟云学术

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Simple and Efficient Knowledge Graph Attention Network for Recommendation

Published:2023-10-20 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Cyber-Physical Social Intelligence (ICCSI)
language:
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Author:

Li Yangding¹,Fu Shaobin¹,Feng Hao¹,Zeng Yangyang¹,Wang Jinghao¹,Jiang Zhihao²,Zhang Lvyun³

Affiliation:

1. Hunan Provincial Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University,School of Information Science and Engineering,Changsha,China

2. Shenzhen Lazada Software Technology Company Limited,Shenzhen,China

3. Hechi University,School of Big Data and Computer Science,Guangxi,China

Funder

National Natural Science Foundation of China

Ministry of Education

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10303765/10303774/10304036.pdf?arnumber=10304036

Reference28 articles.

1. Leveraging Meta-path based Context for Top- N Recommendation with A Neural Co-Attention Model

2. A Knowledge-Aware Attentional Reasoning Network for Recommendation

3. KGAT

4. Knowledge Graph Convolutional Networks for Recommender Systems

5. AGRE: A knowledge graph recommendation algorithm based on multiple paths embeddings RNN encoder

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