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http://dx.doi.org/10.9708/jksci.2022.27.05.037

Design and Implementation of YouTube-based Educational Video Recommendation System  

Kim, Young Kook (Dept. of Software, Soongsil University)
Kim, Myung Ho (Dept. of Software, Soongsil University)
Abstract
As of 2020, about 500 hours of videos are uploaded to YouTube, a representative online video platform, per minute. As the number of users acquiring information through various uploaded videos is increasing, online video platforms are making efforts to provide better recommendation services. The currently used recommendation service recommends videos to users based on the user's viewing history, which is not a good way to recommend videos that deal with specific purposes and interests, such as educational videos. The recent recommendation system utilizes not only the user's viewing history but also the content features of the item. In this paper, we extract the content features of educational video for educational video recommendation based on YouTube, design a recommendation system using it, and implement it as a web application. By examining the satisfaction of users, recommendataion performance and convenience performance are shown as 85.36% and 87.80%.
Keywords
Machine Learning; Deep Learning; Speech Analysis; Recommendation System; System Implementation;
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