A New Rule-Based Approach for Classical Arabic in Natural Language Processing
Named entity recognition (NER) is fundamental in several natural language processing applications. It involves finding and categorizing text into predefined categories such as a person's name, location, and so on. One of the most famous approaches to identify named entity is the rule-based appr...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2022/7164254 |
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| _version_ | 1832565232177774592 |
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| author | Ramzi Salah Muaadh Mukred Lailatul Qadri binti Zakaria Rashad Ahmed Hasan Sari |
| author_facet | Ramzi Salah Muaadh Mukred Lailatul Qadri binti Zakaria Rashad Ahmed Hasan Sari |
| author_sort | Ramzi Salah |
| collection | DOAJ |
| description | Named entity recognition (NER) is fundamental in several natural language processing applications. It involves finding and categorizing text into predefined categories such as a person's name, location, and so on. One of the most famous approaches to identify named entity is the rule-based approach. This paper introduces a rule-based NER method that can be used to examine Classical Arabic documents. The proposed method relied on triggers words, patterns, gazetteers, rules, and blacklists generated by the linguistic information about entities named in Arabic. The method operates in three stages, operational stage, preprocessing stage, and processing the rule application stage. The proposed approach was evaluated, and the results indicate that this approach achieved a 90.2% rate of precision, an 89.3% level of recall, and an F-measure of 89.5%. This new approach was introduced to overcome the challenges related to coverage in rule-based NER systems, especially when dealing with Classical Arabic texts. It improved their performance and allowed for automated rule updates. The grammar rules, gazetteers, blacklist, patterns, and trigger words were all integrated into the rule-based system in this way. |
| format | Article |
| id | doaj-art-519164d77a2048efb7692e4a59f54c81 |
| institution | Kabale University |
| issn | 2314-4785 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Mathematics |
| spelling | doaj-art-519164d77a2048efb7692e4a59f54c812025-02-03T01:08:58ZengWileyJournal of Mathematics2314-47852022-01-01202210.1155/2022/7164254A New Rule-Based Approach for Classical Arabic in Natural Language ProcessingRamzi Salah0Muaadh Mukred1Lailatul Qadri binti Zakaria2Rashad Ahmed3Hasan Sari4Faculty of Information Science and TechnologyFaculty of Information Science and TechnologyFaculty of Information Science and TechnologyICS DepartmentSana’a Community CollegeNamed entity recognition (NER) is fundamental in several natural language processing applications. It involves finding and categorizing text into predefined categories such as a person's name, location, and so on. One of the most famous approaches to identify named entity is the rule-based approach. This paper introduces a rule-based NER method that can be used to examine Classical Arabic documents. The proposed method relied on triggers words, patterns, gazetteers, rules, and blacklists generated by the linguistic information about entities named in Arabic. The method operates in three stages, operational stage, preprocessing stage, and processing the rule application stage. The proposed approach was evaluated, and the results indicate that this approach achieved a 90.2% rate of precision, an 89.3% level of recall, and an F-measure of 89.5%. This new approach was introduced to overcome the challenges related to coverage in rule-based NER systems, especially when dealing with Classical Arabic texts. It improved their performance and allowed for automated rule updates. The grammar rules, gazetteers, blacklist, patterns, and trigger words were all integrated into the rule-based system in this way.http://dx.doi.org/10.1155/2022/7164254 |
| spellingShingle | Ramzi Salah Muaadh Mukred Lailatul Qadri binti Zakaria Rashad Ahmed Hasan Sari A New Rule-Based Approach for Classical Arabic in Natural Language Processing Journal of Mathematics |
| title | A New Rule-Based Approach for Classical Arabic in Natural Language Processing |
| title_full | A New Rule-Based Approach for Classical Arabic in Natural Language Processing |
| title_fullStr | A New Rule-Based Approach for Classical Arabic in Natural Language Processing |
| title_full_unstemmed | A New Rule-Based Approach for Classical Arabic in Natural Language Processing |
| title_short | A New Rule-Based Approach for Classical Arabic in Natural Language Processing |
| title_sort | new rule based approach for classical arabic in natural language processing |
| url | http://dx.doi.org/10.1155/2022/7164254 |
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