Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/394979
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dc.contributor.authorNouf Al Fe'ar-
dc.contributor.authorEinas Al Turki-
dc.contributor.authorAsma Al Zaid-
dc.contributor.authorMashael Al Dubai-
dc.contributor.authorMona Al Sheddi-
dc.contributor.authorNora Al khamees-
dc.contributor.authorNouf Al Drees-
dc.date.accessioned2023-06-15T07:53:09Z-
dc.date.available2023-06-15T07:53:09Z-
dc.identifier.otherukmvital:122646-
dc.identifier.urihttps://ptsldigital.ukm.my/jspui/handle/123456789/394979-
dc.description.abstractIn organizations, a large amount of information exchanges using emails. Therefore, it is important to use text mining to discover knowledge from these unstructured emails. Automatic email classification considered as one of important applications in text mining. It is the process of assigning a text email to one or more predefined classes based on their content. This paper focuses on classifying Arabic and English emails. Since Arabic language is highly inflectional and derivational language, this makes text mining a complex task. In our approach, we first preprocessed data using stemming natural language technique. Then, we used machine learning algorithm to classify emails. We ran an experiment on our approach using real data sets.-
dc.language.isoeng-
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE),Piscataway, US-
dc.subjecte-Classifier-
dc.subjectBi-lingual email-
dc.titlee-Classifier: a bi-lingual email classification system-
dc.typeSeminar Papers-
dc.format.pages4-
dc.identifier.callnoT58.5.C634 2008 kat sem j.2-
dc.contributor.conferencenameInternational Symposium on Information Technology-
dc.coverage.conferencelocationKuala Lumpur Convention Centre-
dc.date.conferencedate26/08/2008-
Appears in Collections:Seminar Papers/ Proceedings / Kertas Kerja Seminar/ Prosiding

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