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2016 (Vol. 13, Issue: 12)
Research Article

Building Words Dictionary List Using Symbol Enumeration and Hashing Methodology

Safa S. Abdul-Jabbar and Dr. Loay E. George
Computer Science Department, College of Science, Baghdad University, Baghdad, Iraq

DOI: 10.19026/rjaset.13.3761
Submitted Accepted Published
September 23, 2016 November 15, 2016 December 15, 2016

  How to Cite this Article:

Safa S. Abdul-Jabbar and Dr. Loay E. George, 2016. Building Words Dictionary List Using Symbol Enumeration and Hashing Methodology.  Research Journal of Applied Sciences, Engineering and Technology, 13(12): 885-894.

DOI: 10.19026/rjaset.13.3761

URL: http://www.maxwellsci.com/jp/mspabstract.php?jid=RJASET&doi=rjaset.13.3761


This study aims to introduce a new method to reduce the time needed for text retrieval systems by building word dictionary takes the advantage of enumerating each string, multi hashing methodology stop-words extraction and word stemming; dictionary-based text mining has an important role in understanding and analyzing large text datasets that used in any searching, matching and information retrieval systems. All of these systems mainly imply dealing with strings (i.e., undefined number of alphabet characters of each word and an undefined number of words in a sentence) and text processing operation. This has a significant effect on the execution time for the systems due to the overhead hidden-operations (like, symbols matching calculations and character conversion operations). Some of the attained experimental results are provided for these operations with a comparison between the proposed method results and those belong to the traditional method; which directly deals with strings only. Results comparisons are provided for each step to understand the advantage of the proposed approach. The results demonstrate the effectiveness of the proposed approach that reduces the execution time for each step, which in turn leads to improve the overall execution time for the whole system while maintaining the accuracy of the operations.

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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.


© The Author(s) 2016

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