Improving Transformer-based Sequential Recommenders through Preference Editing
One of the key challenges in sequential recommendation is how to extract and represent user preferences. Traditional methods rely solely on predicting the next item. But user behavior may be driven by complex preferences. Therefore, these methods cannot make accurate recommendations when the availab...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Association for Computing Machinery
2023
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| Subjects: | |
| Online Access: | View Fulltext in Publisher View in Scopus |