MULTIMODAL RECOMMENDATION SYSTEMS: ENHANCING RECOMMENDATION QUALITY THROUGH DATA FUSION
Аннотация
In today's digital age, users interact with platforms using varied content types—text, images, audio, and even video. Capturing the essence of this diverse data for recommendation can yield richer user profiles and more relevant suggestions. This paper investigates the potential of Multimodal Recommendation Systems, which integrate information from multiple sources to enhance recommendation quality. We delve into methods for data fusion, the challenges of multimodal systems, and their application across different sectors.
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