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Finding the similarity between two Arabic texts
Other Title(s)
إيجاد نسبة التشابه ما بين نصين عربيين
Joint Authors
Abd al-Amir, Asil Qasim
Kazim, Suhad Mal Allah
Source
Issue
Vol. 58, Issue 1A (31 Mar. 2017), pp.152-162, 11 p.
Publisher
University of Baghdad College of Science
Publication Date
2017-03-31
Country of Publication
Iraq
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
Calculating similarities between texts that have been written in one language or multiple languages still one of the most important challenges facing the natural language processing.
This work offers many approaches that used for the texts similarity.
The proposed system will find the similarity between two Arabic texts by using hybrid similarity measures techniques: Semantic similarity measure, Cosine similarity measure and N-gram ( using the Dice similarity measure).
In our proposed system we will design Arabic SemanticNet that store the keywords for a specific field(computer science), by this network we can find semantic similarity between words according to specific equations.
Cosine and N-gram similarity measures are used in order to find the similar characters sequences.
The proposed system was executed by using Visual Basic 2012, and after testing it, it proved to be a worthy for finding the similarity between two Arabic texts (From the viewpoint of accuracy and search time).
American Psychological Association (APA)
Kazim, Suhad Mal Allah& Abd al-Amir, Asil Qasim. 2017. Finding the similarity between two Arabic texts. Iraqi Journal of Science،Vol. 58, no. 1A, pp.152-162.
https://search.emarefa.net/detail/BIM-732943
Modern Language Association (MLA)
Kazim, Suhad Mal Allah& Abd al-Amir, Asil Qasim. Finding the similarity between two Arabic texts. Iraqi Journal of Science Vol. 58, no. 1A (2017), pp.152-162.
https://search.emarefa.net/detail/BIM-732943
American Medical Association (AMA)
Kazim, Suhad Mal Allah& Abd al-Amir, Asil Qasim. Finding the similarity between two Arabic texts. Iraqi Journal of Science. 2017. Vol. 58, no. 1A, pp.152-162.
https://search.emarefa.net/detail/BIM-732943
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 161-162
Record ID
BIM-732943