Impact of temporal context on recommender systems along global timeline
Recommender systems filter through the vast pool of information and provide personalized recommendations. However, with the dynamic nature of user preference, it is essential to design recommender systems that can adapt to the continuous changes in user preferences and the evolving environment. In...
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| Format: | Thesis-Doctor of Philosophy |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/173690 |