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    Abstract
2017 (Vol. 14, Issue: 9)
Research Article

Graph-Based Text Representation: A Survey of Current Approaches

1Geehan Sabah Hassan, 1Asma Khazaal Abdulsahib and 2Siti Sakira Kamaruddin
1College of Education for Human Science-Ibn Rushd, University of Baghdad, Baghdad, Iraq
2School of Computing, Universiti Utara Malaysia, 06010 UUM Sintok, Malaysia
 

DOI: 10.19026/rjaset.14.5073
Submitted Accepted Published
May 4, 2017 July 6, 2017 September 15, 2017

  How to Cite this Article:

1Geehan Sabah Hassan, 1Asma Khazaal Abdulsahib and 2Siti Sakira Kamaruddin, 2017. Graph-Based Text Representation: A Survey of Current Approaches.  Research Journal of Applied Sciences, Engineering and Technology, 14(9): 334-340.

DOI: 10.19026/rjaset.14.5073

URL: http://www.maxwellsci.com/jp/mspabstract.php?jid=RJASET&doi=rjaset.14.5073

Abstract:


Lately, we have seen the problem of sparsity data has increased due to the increase in the amount of available documentation on the Internet, to take care of this issue need to choose the best strategy for the representation of the content. In recent years, scientists have been switched to the representation of the content graphically. Because the results of previous studies proved that the represented data as graphs reduce the problem of sparse data. So this study aims to review the sorts of graphs used to represent the content of documents. Were the exploratory outcomes recommended that our methodologies are superior to other methodologies in each of the synthetic global data sets and the real.

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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.

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© The Author(s) 2017

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