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Abstract
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Article Information:
Generation of Tag Clouds for E-learning Documents-a Value-added Service to Peer Learners
M. Ravichandran and G. Kulanthaivel
Corresponding Author: M. Ravichandran
Submitted: October 29, 2014
Accepted: December 18, 2014
Published: May 20, 2015 |
Abstract:
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In an E-learning environment users (learners/facilitators) have access to a large collection of learning documents stored in various online databases. Retrieving the most relevant learning documents available on database-driven websites is often difficult, as great amounts of textual content is involved. A peer learner may require a general sketch of the digital document content available in the database in order to find out whether the document information is useful for his/her search requirements. In this research study, we present a method for generating tag clouds for E-learning documents as a value added service to peer learners. We propose a system that generates the cluster summary of e-learning document and provides visual representation of these documents stored in a database. Visualization of the content of the database can be helpful during the peer learners search process and to reach their study goals, thus serving as a value-added service. The uniqueness of this method is that it reveals the fundamental structure that provides the text document with certain semantics and is capable of retrieving the most appropriate information. The relationship between the tags is obtained using the Multi Objective Hierarchical Cluster (MOHC) technique. In this study, we tested our proposed method using different datasets and present the tag clouds obtained by the computations for each dataset. The experimental results of tag cloud generation for e-learning documents demonstrate the accuracy and effectiveness of our proposed approach.
Key words: Document search, E-learning, tag cloud, visualization, , ,
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Cite this Reference:
M. Ravichandran and G. Kulanthaivel, . Generation of Tag Clouds for E-learning Documents-a Value-added Service to Peer Learners . Research Journal of Applied Sciences, Engineering and Technology, (2): 206-213.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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