期刊论文详细信息
Pakistan Journal of Engineering & Technology
YouTube Video Recommendation Based Multi-lingual Feedback
Muhammad Abubakar Siddique1  Muhammad Ali Javaid2  Muhammad Kahsan Akram2  Mutiullah Jamil2  Abdullah Haider2 
[1] Khwaja Fareed University of Engineering and Information Technology, Pakistan;Khwaja Freed University of Engineering and Information Technology Rahim Yar Khan, Pakistan ;
关键词: youtube;    multi-language comments;    polarity;    sentiment score;   
DOI  :  
来源: DOAJ
【 摘 要 】

Today YouTube is the first one application when the people need to learn something this is due to the robust service of the YouTube. Every second 500Hours video uploaded on the YouTube. On the one side this huge data is so big edge for YouTube but on the other side this is the big challenge for YouTube to provide efficient and effective search results for each user. People when search on the YouTube they are facing the difficulty to find the best video matched with their required content the only way to find the quality of the video is user feedback in term of comments but we also faced some problem too in comments most important are these two we focus1.Huge comments 2.Multi-language comments for this problem our proposed method help the user to processes the all comments into the single English language and find the sentiment of the each video category and one the basis of the polarity score we find the best video tutorial and also compare the polarity results with and without our proposed method the results shows the method is effective and efficient.

【 授权许可】

Unknown   

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