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While most search and recommendation algorithms work well, they rely heavily on your sensitive information, such as your viewing history, search history, and internet browser cookies.
This can lead to inaccurate recommendations if a user deletes their information or, depending on their level of privacy, lacks the necessary information to make a recommendation, a cold start problem that occurs in most recommendation systems.
In addition, since metadata is added by the content creator or distributor, there is a possibility that information about the actual content is excluded, reducing the accuracy of search or recommendation, or being abused.
Currently, similar content recommendation systems on OTT platforms often exclude key content that could be spoilers, even if the plot is included in the recommendation process.
This can cause users to lose trust in the recommendation system if the actual content is different, even if it is recommended as similar simply because of a similar genre or visual atmosphere. |
IEEE/ICACT20240357 Slide.06
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