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  • 标题:Improving the methods of email classification based on words ontology
  • 本地全文:下载
  • 作者:Foruzan Kiamarzpour ; Rouhollah Dianat ; Mohammad Bahrani
  • 期刊名称:International Journal of Computer Science Issues
  • 印刷版ISSN:1694-0784
  • 电子版ISSN:1694-0814
  • 出版年度:2013
  • 卷号:10
  • 期号:4
  • 出版社:IJCSI Press
  • 摘要:people and made the valuable information available for the users. Email is the service, which the Internet provides today for its own users; this service has attracted most of the users' attention due to the low cost. Along with the numerous benefits of Email, one of the weaknesses of this service is that the number of received emails is continually being enhanced, thus the ways are needed to automatically filter these disturbing letters. Most of these filters utilize a combination of several techniques such as the Black or white List, using the keywords and so on in order to identify the spam more accurately In this paper, we introduce a new method to classify the spam. We are seeking to increase the accuracy of Email classification by combining the output of several decision trees and the concept of ontology.
  • 关键词:Data Mining; Email classification; spam detection; decision tree; ontology
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