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First is Abstract.
We proposes an AI-based Video Metadata Extension Model to overcome the limitations of video search and recommendation systems in the multimedia industry.
Current video searches and recommendations utilize pre-added metadata.
Metadata includes filenames, keywords, tags, genres, and other things.
This makes it impossible to make direct predictions about the content of a video without pre-added metadata.
These platforms also analyze your previous search history, viewing history, and so on, to understand your interests in order to serve you personalized videos.
This may not reflect the actual content and may raise privacy concerns.
In addition, recommendation systems suffer from a cold start problem, which is the lack of an initial target, as well as a bubble effect. |
IEEE/ICACT20240357 Slide.02
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