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Classification of Education Videos from You Tube using User Generated Data


Affiliations
1 Department of Information Technology, B.S.Abdur Rahman University, Vandalur, Chennai-600048, India
2 Department of Information Technology, B.S.Abdur Rahman University, Vandalur, Chennai-600048, India
3 Department of Computer Science and Engineering, B.S.Abdur Rahman University, Vandalur, Chennai-600048, India
     

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Edutube includes video sharing sites, wikis, blogs, web applications. A Edutube site allows user to search educational videos .The system proposed is to classifying the education videos in online video sharing sites based on the user generated information. The categorization of videos can be done, i.e. the text features are combined with the visual features from the images using various classification techniques (K-means, SVM).This feature will enhance the precision and efficiency of the system to the greater extent. In this paper we have proposed and the implementation based on the text features like User Generated Data, Title and Description. Based on this idea three text feature are concentrated for this purpose. They are lexical features, syntactic features and semantic features. We use information gain for feature extraction and k-means and svm techniques for classification. Find the efficiency of videos by using kmeans algorithm then collect the results and apply SVM algorithm to improve its efficiency. This paper describes the system to find relevant (educational) videos in the Edutube.


Keywords

Education Video, Video Sharing, Edutube, SVM, KMeans.
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  • Classification of Education Videos from You Tube using User Generated Data

Abstract Views: 256  |  PDF Views: 1

Authors

M. Induja
Department of Information Technology, B.S.Abdur Rahman University, Vandalur, Chennai-600048, India
C. Vijayalakshmi
Department of Information Technology, B.S.Abdur Rahman University, Vandalur, Chennai-600048, India
G. Sivapriya
Department of Computer Science and Engineering, B.S.Abdur Rahman University, Vandalur, Chennai-600048, India

Abstract


Edutube includes video sharing sites, wikis, blogs, web applications. A Edutube site allows user to search educational videos .The system proposed is to classifying the education videos in online video sharing sites based on the user generated information. The categorization of videos can be done, i.e. the text features are combined with the visual features from the images using various classification techniques (K-means, SVM).This feature will enhance the precision and efficiency of the system to the greater extent. In this paper we have proposed and the implementation based on the text features like User Generated Data, Title and Description. Based on this idea three text feature are concentrated for this purpose. They are lexical features, syntactic features and semantic features. We use information gain for feature extraction and k-means and svm techniques for classification. Find the efficiency of videos by using kmeans algorithm then collect the results and apply SVM algorithm to improve its efficiency. This paper describes the system to find relevant (educational) videos in the Edutube.


Keywords


Education Video, Video Sharing, Edutube, SVM, KMeans.



DOI: https://doi.org/10.36039/ciitaas%2F5%2F3%2F2013%2F106829.108-113