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dc.contributor.authorAl-Ahmari, S. Saad
dc.contributor.authorAbdullatif Al-Johar, B.
dc.date.accessioned2016-08-10T12:27:00Z
dc.date.available2016-08-10T12:27:00Z
dc.date.issued2016-07-11
dc.identifier.citationS. Saad Al-Ahmari and B. Abdullatif Al-Johar " Cross domains Arabic named entity recognition system ", Proc. SPIE 10011, First International Workshop on Pattern Recognition, 100111I (July 11, 2016); doi:10.1117/12.2240887; http://dx.doi.org/10.1117/12.2240887
dc.identifier.doi10.1117/12.2240887
dc.identifier.urihttp://hdl.handle.net/10754/618211
dc.description.abstractNamed Entity Recognition (NER) plays an important role in many Natural Language Processing (NLP) applications such as; Information Extraction (IE), Question Answering (QA), Text Clustering, Text Summarization and Word Sense Disambiguation. This paper presents the development and implementation of domain independent system to recognize three types of Arabic named entities. The system works based on a set of domain independent grammar-rules along with Arabic part of speech tagger in addition to gazetteers and lists of trigger words. The experimental results shown, that the system performed as good as other systems with better results in some cases of cross-domains corpora. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
dc.publisherSPIE-Intl Soc Optical Eng
dc.relation.urlhttp://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2240887
dc.rightsCopyright 2016 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
dc.titleCross domains Arabic named entity recognition system
dc.typeConference Paper
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.identifier.journalFirst International Workshop on Pattern Recognition
dc.conference.dateMay 11, 2016
dc.conference.nameFirst International Workshop on Pattern Recognition
dc.conference.locationTokyo, Japan
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionComputer Science Department, King Faisal University, Hofuf-Al-Hassa-31982,Kingdom of Saudi Arabia
kaust.personAl-Ahmari, S. Saad
refterms.dateFOA2018-06-14T08:22:55Z


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