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Classification of Education Videos from You Tube using User Generated Data

M. Induja, C. Vijayalakshmi, G. Sivapriya


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.


Education Video, Video Sharing, Edutube, SVM, KMeans

Full Text:



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