Multi-Behavior Enhanced Heterogeneous Graph Convolutional Networks Recommendation Algorithm based on Feature-Interaction
Graph convolution neural networks have shown powerful ability in recommendation, thanks to extracting the user-item collaboration signal from users' historical interaction information. However, many existing studies often learn the final embedded representation of items and users through IDs of...
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| Published in: | Applied artificial intelligence Vol. 37; no. 1 |
|---|---|
| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Philadelphia
Taylor & Francis
31.12.2023
Taylor & Francis Ltd Taylor & Francis Group |
| Subjects: | |
| ISSN: | 0883-9514, 1087-6545 |
| Online Access: | Get full text |
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