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     Research Journal of Applied Sciences, Engineering and Technology


Presentation Mining: An Overview of Information Extraction Systems

1Vinothini Kasinathan and 1, 2Aida Mustapha
1Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia
2Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia Parit Raja, 86400 Batu Pahat, Johor, Malaysia
Research Journal of Applied Sciences, Engineering and Technology   2015  3:308-314
http://dx.doi.org/10.19026/rjaset.11.1721  |  © The Author(s) 2015
Received: February ‎3, ‎2015  |  Accepted: March ‎20, ‎2015  |  Published: September 25, 2015

Abstract

In education, scanning through endless slides in PowerPoint presentation is highly ineffective especially for the Digital Natives due to their multi-modal learning style. In order to cater for the high volume of information emerging from printed alphabets to digital images, this study proposes a text mining approach to extract keywords from a collection of presentation slides in a similar topic. This approach is to support the existing architecture of presentation mapping, whereby the keywords extracted would then be reconstructed visually in the form of visual knowledge display. In achieving this, this study provides a general discussion of text mining technologies available and later focuses on different keyword extraction systems. Finally, this study introduces the frontier method of this field, which is presentation mining.

Keywords:

Natural language processing, powerpoint, text mining,


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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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