Autoregressive Decoder With Extracted Gap Sessions for Sequential/Session-Based Recommendation
Learning the complex relationships between items in a sequential recommendation system (SRS) and session-based recommendation system (SBRS) is critical for obtaining higher prediction scores. In recent studies, to capture item-item information, items have been represented as the nodes of graph neura...
| Published in: | IEEE Access |
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| Main Authors: | , , |
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10189391/ |
