Clustering and Classification of Email Contents
| المصدر: | مجلة جامعة الملك سعود - علوم الحاسب والمعلومات |
|---|---|
| الناشر: | جامعة الملك سعود |
| المؤلف الرئيسي: | Alsmadi, Izzat (Author) |
| مؤلفين آخرين: | Alhami, Ikdam (Co-Author) |
| المجلد/العدد: | مج27, ع1 |
| محكمة: | نعم |
| الدولة: |
السعودية |
| التاريخ الميلادي: |
2015
|
| الصفحات: | 46 - 57 |
| DOI: |
10.33948/0584-027-001-005 |
| ISSN: |
1319-1578 |
| رقم MD: | 973502 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | science |
| مواضيع: | |
| كلمات المؤلف المفتاحية: |
Emails Classification | Document Similarity | Document Classification | Feature Extraction | Subject Classification | Content Classification
|
| رابط المحتوى: |
| المستخلص: |
Information users depend heavily on emails’ system as one of the major sources of communication. Its importance and usage are continuously growing despite the evolution of mobile applications, social networks, etc. Emails are used on both the personal and professional levels. They can be considered as official documents in communication among users. Emails’ data mining and analysis can be conducted for several purposes such as: Spam detection and classification, subject classification, etc. In this paper, a large set of personal emails is used for the purpose of folder and subject classifications. Algorithms are developed to perform clustering and classification for this large text collection. Classification based on NGram is shown to be the best for such large text collection especially as text is Bi-language (i.e. with English and Arabic content). |
|---|---|
| ISSN: |
1319-1578 |
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