{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T10:48:58Z","timestamp":1782989338198,"version":"3.54.5"},"reference-count":59,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2013,10,16]],"date-time":"2013-10-16T00:00:00Z","timestamp":1381881600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Information Science"],"published-print":{"date-parts":[[2014,2]]},"abstract":"<jats:p>In this paper, we propose a hybrid named entity recognition (NER) approach that takes the advantages of rule-based and machine learning-based approaches in order to improve the overall system performance and overcome the knowledge elicitation bottleneck and the lack of resources for underdeveloped languages that require deep language processing, such as Arabic. The complexity of Arabic poses special challenges to researchers of Arabic NER, which is essential for both monolingual and multilingual applications. We used the hybrid approach to develop an Arabic NER system that is capable of recognizing 11 types of Arabic named entities: Person, Location, Organization, Date, Time, Price, Measurement, Percent, Phone Number, ISBN and File Name. Extensive experiments were conducted using decision trees, Support Vector Machines and logistic regression classifiers to evaluate the system performance. The empirical results indicate that the hybrid approach outperforms both the rule-based and the ML-based approaches when they are processed independently. More importantly, our system outperforms the state-of-the-art of Arabic NER in terms of accuracy when applied to ANERcorp standard dataset, with F-measures 0.94 for Person, 0.90 for Location and 0.88 for Organization.<\/jats:p>","DOI":"10.1177\/0165551513502417","type":"journal-article","created":{"date-parts":[[2013,10,17]],"date-time":"2013-10-17T00:25:45Z","timestamp":1381969545000},"page":"67-87","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":57,"title":["A hybrid approach to Arabic named entity recognition"],"prefix":"10.1177","volume":"40","author":[{"given":"Khaled","family":"Shaalan","sequence":"first","affiliation":[{"name":"The British University in Dubai, Dubai International Academic City, UAE"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mai","family":"Oudah","sequence":"additional","affiliation":[{"name":"The British University in Dubai, Dubai International Academic City, UAE"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2013,10,16]]},"reference":[{"key":"bibr1-0165551513502417","doi-asserted-by":"publisher","DOI":"10.1075\/li.30.1.03nad"},{"key":"bibr2-0165551513502417","doi-asserted-by":"publisher","DOI":"10.1145\/234173.234209"},{"key":"bibr3-0165551513502417","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2009.2019927"},{"key":"bibr4-0165551513502417","first-page":"1","author":"Babych B","year":"2003","journal-title":"Proceedings of the 7th international EAMT workshop on MT and other language technology tools, improving MT through other language technology tools: resources and tools for building MT (EAMT 2003)"},{"key":"bibr5-0165551513502417","unstructured":"Abouenour L, Bouzoubaa K, Rosso P. 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