Email this article 
Open Access
Subscription or Fee Access
Classification of Education Videos from You Tube using User Generated Data
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
References
Hong Qing Yu, Carlos Pedrinaci, Stefan Dietze, and John Domingue
“Using Linked Data to Annotate and Search Educational Video
Resources for Supporting Distance Learning” IEEE transactions on
learning technologies, vol. 5, no. 2, April-June 2012.
Surendar Chandra “Experiences in personal lecture video capture ieée
transaction ns on learning technologies”, vol. 4, no. 3, july-september
Konstantinos Antonis, Thanasis Daradoumis, Spyros Papadakis, and
Christos Simos” Evaluation of the Effectiveness of a Web-Based
Learning Design for Adult Computer Science Courses” ieee transactions
on education, vol. 54, no. 3, august 2011.
Mihaela Cocea and Stephan Weibelzahl “Disengagement Detection in
Online Learning: Validation Studies and Perspectives” ieee transactions
on learning technologies, vol. 4, no. 2, april-june 2011.
R.Priyadharsni,Y.Nawaz Ahmed Khan and T.Panimozhipavai,” web 2.o
Based Classification Of Extremist Videos in Online Video Sharing Sites
Using User Generated Data”ICICT December 2010.
S. Wei, Y. Zhao, Z. Zhu, and N. Liu, “Multimodal Fusion for Video
Search Reranking, It,” IEEE Trans. Knowledge and Data Eng., vol.
,no. 8,Aug. 2010.
L. Ballan, M. Bertini, A.D. Bimbo, and G. Serra, “Video Annotation and
Retrieval Using Ontologies and Rule Learning,” IEEE Multimedia,vol.
, Oct.-Dec. 2010.
Yoshinaga, Nobuhara “Formal concept analysis based web pages
classification/visualization and their application to information retrieval
“Communication and Information Technology (ISICT) 2010.
G. Vanderburg, “Clojure Templating Libraries: Fleet and Enlive,” IEEE
Internet Computing, vol. 14, no. 5, pp. 87-90, Sept-Oct. 2010.
Yusuf Aytar , Mubarak Shah , Jiebo Luo Computer Vision Lab,
University of Central Florida” Utilizing Semantic Word Similarity
Measures for Video Retrieval”IEEE society August 2008.
A. Ahmed and H. Chen, “Whiteprints: A stylometric approach to
identity-level identification and similarity detection in cyberspace,”
ACM Transactions on Information Systems, 26(2): 1-29, 2008.
H. Chen, E. Reid and A. Salem “Multimedia content coding and
analysis: Unravelling the content of Jihadi extremist groups' videos,”
Studies in Conflict & Terrorism 31(7): 605 – 626, 2008.
H. Chen, T. Fu and S. Thoms “Cyber extremism in Web 2.0: An
exploratory study of international Jihadist groups,” IEEE International
Conference on Intelligence and Security Informatics 2008, pp. 98-103,
T.-D. Wu, Y.-Y. Yeh, and Y.-M. Chou, “Video Learning Object
Extraction and Standardized Metadata,” Proc. Int’l Conf. Computer
Science and Software Eng., vol. 6, pp. 332-335, 2008.
C. R. Sunstein, "Neither Hayek nor Habermas," Public Choice, vol.
,pp. 87-95, 2008.
T. O'Reilly, “What Is Web 2.0: Design patterns and business models for
the next generation of software,” Communications and Strategies, vol.
, pp. 17-37, 2007.
C.-H. Hsieh, M.-H. Hung and C.-M.Kuo “Rule-based event detection of
broadcast baseball videos using mid-level cues,” Proceedings of the
Second International Conference on Innovative Computing, Information
and Control, IEEE Computer Society, 2007.
M. Chau and J. Xu, “Mining communities and their relationships in
blogs: A study of online hate groups,” International Journal of Human-
Computer Studies 65: 57-70, 2007.
J. Broekstra, A. Kampman, and F.V. Harmelen, “Sesame: A Generic
Architecture for Storing and Querying RDF and RDFSchema,” Proc.
First Int’l Semantic Web Conf. the Semantic Web,pp. 54-68, 2002.
DOI: http://dx.doi.org/10.36039/AA062013004
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.