Federated learning-driven collaborative recommendation system for multi-modal art analysis and enhanced recommendations
With the rapid development of artificial intelligence technology, recommendation systems have been widely applied in various fields. However, in the art field, art similarity search and recommendation systems face unique challenges, namely data privacy and copyright protection issues. To address the...
| Published in: | PeerJ Computer Science |
|---|---|
| Main Author: | |
| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2024
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210759435&doi=10.7717%2fpeerj-cs.2405&partnerID=40&md5=7418e8fcf0f994d59a2204bd6441ef4e |