Video Recommendation System for YouTube Considering Users Feedback
Video Recommendation System for YouTube Considering Users Feedback
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youtube video recommendation system
weighted attribute based video recommendation system
youtube watch-list recommendation
youtube video suggestion

How to Cite

Md. Shamim Reza Sajib, Md. Ariful Islam Malik, & Md. Ashraful Islam. (2018). Video Recommendation System for YouTube Considering Users Feedback. Global Journal of Computer Science and Technology, 18(G1), 11–15. Retrieved from


Youtube is the most video sharing and viewing platform in the world As there are many people of different tastes hundreds of categories of videos can be found on YouTube while thousands of videos of each So when the site recommends videos for a user it takes some issues which fill the needs of the user Most of the time a user watches videos related to the previously watched video But sometimes user s mood changes with time or weather A user may not hear a song in the whole year but can search the song on a rainy day Another case a user may watch some types of videos at day but another type of videos at night or another at midnight In this paper we propose a recommendation system considering some attributes like weather time month to understand the dynamic mood of a user Each attribute is assigned a weight calculated by performing a survey on some YouTube users Most recently viewed videos is assigned heavy weight and weather is assigned lower This recommendation system will make YouTube more user-friendly dynamic and acceptable
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