A Survey on Multimodal Recommender Systems: Recent Advances and Future Directions
University of Hong Kong · Hong Kong Polytechnic University · +2 more institutions
Abstract
The exponential growth of online information has made it increasingly difficult for users to identify valuable and relevant content. Recommender systems have emerged as a critical solution to this challenge by tailoring content to individual preferences. With the proliferation of diverse multimedia services, human interaction with the digital world has become inherently multimodal. Consequently, recommender systems capable of comprehending and interpreting multimodal information can more effectively align with individual preferences. With its recent surge in research attention, the field of multimodal recommender systems (MRS) still lacks a comprehensive technical survey. Existing surveys suffer from two…
Citation impact
- FWCI
- 408.46
- Percentile
- 100%
- References
- 0
Authors
8- JXJinfeng XuCorresponding
University of Hong Kong
- ZCZheyu Chen
Hong Kong Polytechnic University
- SYShuo Yang
University of Hong Kong
- JLJinze Li
University of Hong Kong
- WWWei Wang
Shenzhen MSU-BIT University
Topics & keywords
- Recommender system
- Field (mathematics)
- Focus (optics)
- Bridge (graph theory)
- Feature (linguistics)
- Exploit