Using Graph Mining Method in Analyzing Turkish Loanwords Derived from Arabic Language
Loanwords are the words transferred from one language to another, which become essential part of the borrowing language. The loanwords have come from the source language to the recipient language because of many reasons. Detecting these loanwords is complicated task due to that there are no standar...
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| Format: | Article |
| Language: | Arabic |
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College of Science for Women, University of Baghdad
2022-12-01
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| Series: | Baghdad Science Journal |
| Subjects: | |
| Online Access: | https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/6008 |
| _version_ | 1811185625712295936 |
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| author | Abbood Kirebut Jassim Muneam Jabbar Hamzah Ahmed Hussein Aliwy |
| author_facet | Abbood Kirebut Jassim Muneam Jabbar Hamzah Ahmed Hussein Aliwy |
| author_sort | Abbood Kirebut Jassim |
| collection | DOAJ |
| description |
Loanwords are the words transferred from one language to another, which become essential part of the borrowing language. The loanwords have come from the source language to the recipient language because of many reasons. Detecting these loanwords is complicated task due to that there are no standard specifications for transferring words between languages and hence low accuracy. This work tries to enhance this accuracy of detecting loanwords between Turkish and Arabic language as a case study. In this paper, the proposed system contributes to find all possible loanwords using any set of characters either alphabetically or randomly arranged. Then, it processes the distortion in the pronunciation, and solves the problem of the missing letters in Turkish language relative to Arabic language. A graph mining technique was introduced, for identifying the Turkish loanwords from Arabic language, which is used for the first time for this purpose. Also, the problem of letters differences, in the two languages, is solved by using a reference language (English) to unify the style of writing. The proposed system was tested using 1256 words that manually annotated. The obtained results showed that the f-measure is 0.99 which is high value for such system. Also, all these contributions lead to decrease time and effort to identify the loanwords in efficient and accurate way. Moreover, researchers do not need to have knowledge in the recipient and the source languages. In addition, this method can be generalized to any two languages using the same steps followed in obtaining Turkish loanwords from Arabic.
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| first_indexed | 2024-04-11T13:32:25Z |
| format | Article |
| id | doaj.art-9773eab31dd94fc19a900866e4b89fb9 |
| institution | Directory Open Access Journal |
| issn | 2078-8665 2411-7986 |
| language | Arabic |
| last_indexed | 2024-04-11T13:32:25Z |
| publishDate | 2022-12-01 |
| publisher | College of Science for Women, University of Baghdad |
| record_format | Article |
| series | Baghdad Science Journal |
| spelling | doaj.art-9773eab31dd94fc19a900866e4b89fb92022-12-22T04:21:45ZaraCollege of Science for Women, University of BaghdadBaghdad Science Journal2078-86652411-79862022-12-0119610.21123/bsj.2022.6008Using Graph Mining Method in Analyzing Turkish Loanwords Derived from Arabic LanguageAbbood Kirebut Jassim0Muneam Jabbar Hamzah1Ahmed Hussein Aliwy2Department of Computer of Science, College of Science for Women, University of Baghdad, Baghdad, IraqDepartment of Computer of Science, College of Science for Women, University of Baghdad, Baghdad, IraqDepartment of Computer of Science, Faculty Computer Science and mathematics, University of Kufa, Najaf, Iraq. Loanwords are the words transferred from one language to another, which become essential part of the borrowing language. The loanwords have come from the source language to the recipient language because of many reasons. Detecting these loanwords is complicated task due to that there are no standard specifications for transferring words between languages and hence low accuracy. This work tries to enhance this accuracy of detecting loanwords between Turkish and Arabic language as a case study. In this paper, the proposed system contributes to find all possible loanwords using any set of characters either alphabetically or randomly arranged. Then, it processes the distortion in the pronunciation, and solves the problem of the missing letters in Turkish language relative to Arabic language. A graph mining technique was introduced, for identifying the Turkish loanwords from Arabic language, which is used for the first time for this purpose. Also, the problem of letters differences, in the two languages, is solved by using a reference language (English) to unify the style of writing. The proposed system was tested using 1256 words that manually annotated. The obtained results showed that the f-measure is 0.99 which is high value for such system. Also, all these contributions lead to decrease time and effort to identify the loanwords in efficient and accurate way. Moreover, researchers do not need to have knowledge in the recipient and the source languages. In addition, this method can be generalized to any two languages using the same steps followed in obtaining Turkish loanwords from Arabic. https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/6008Arabic language, Data mining, Graph mining, Loanwords, Turkish language |
| spellingShingle | Abbood Kirebut Jassim Muneam Jabbar Hamzah Ahmed Hussein Aliwy Using Graph Mining Method in Analyzing Turkish Loanwords Derived from Arabic Language Baghdad Science Journal Arabic language, Data mining, Graph mining, Loanwords, Turkish language |
| title | Using Graph Mining Method in Analyzing Turkish Loanwords Derived from Arabic Language |
| title_full | Using Graph Mining Method in Analyzing Turkish Loanwords Derived from Arabic Language |
| title_fullStr | Using Graph Mining Method in Analyzing Turkish Loanwords Derived from Arabic Language |
| title_full_unstemmed | Using Graph Mining Method in Analyzing Turkish Loanwords Derived from Arabic Language |
| title_short | Using Graph Mining Method in Analyzing Turkish Loanwords Derived from Arabic Language |
| title_sort | using graph mining method in analyzing turkish loanwords derived from arabic language |
| topic | Arabic language, Data mining, Graph mining, Loanwords, Turkish language |
| url | https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/6008 |
| work_keys_str_mv | AT abboodkirebutjassim usinggraphminingmethodinanalyzingturkishloanwordsderivedfromarabiclanguage AT muneamjabbarhamzah usinggraphminingmethodinanalyzingturkishloanwordsderivedfromarabiclanguage AT ahmedhusseinaliwy usinggraphminingmethodinanalyzingturkishloanwordsderivedfromarabiclanguage |