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     Research Journal of Applied Sciences, Engineering and Technology


Generation of Tag Clouds for E-learning Documents-a Value-added Service to Peer Learners

1M. Ravichandran and 2G. Kulanthaivel
1Department of Computer Science and Engineering, Sathyabama University
2Department of Electronics Engineering, NITTTR, Taramani, Chennai, Tamilnadu, India
Research Journal of Applied Sciences, Engineering and Technology  2015  2:206-213
http://dx.doi.org/10.19026/rjaset.10.2573  |  © The Author(s) 2015
Received: October ‎29, ‎2014  |  Accepted: December ‎18, ‎2014  |  Published: May 20, 2015

Abstract

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.

Keywords:

Document search, E-learning , tag cloud, visualization,


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Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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