• DocumentCode
    3508846
  • Title

    Content Based Spam Text Classification: An Empirical Comparison between English and Chinese

  • Author

    Liumei Zhang ; Jianfeng Ma ; Yichuan Wang

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Xi´an Shiyou Univ., Xi´an, China
  • fYear
    2013
  • fDate
    9-11 Sept. 2013
  • Firstpage
    69
  • Lastpage
    76
  • Abstract
    Spam text including e-mails, SMS and etc, is a real and growing problem primarily due to the availability of digital handset and internet. To filter spam text is to be the utmost topic over varies study area. Text bodies of different forms of communication expose channel for spammers. In this study, text dataset in English and Chinese are pre-processed. Classical classifiers are applied on the pre-processed dataset to evaluate the accuracy of the same classifier. The behavior of classifiers among English and Chinese is evaluated. The paper also discussed the result of experiments. In addition, different from most existing text spam detection methods which are based on English, classifiers suited for English text classification is insufficient for Chinese text classification.
  • Keywords
    information filtering; natural language processing; pattern classification; text analysis; unsolicited e-mail; Chinese text classification; Chinese text dataset; English text classification; English text dataset; classical classifiers; content based spam text classification; spam text filtering; text spam detection methods; Accuracy; Educational institutions; Entropy; Frequency measurement; Training; Unsolicited electronic mail; classification; datamining; machine learning; spam text;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Networking and Collaborative Systems (INCoS), 2013 5th International Conference on
  • Conference_Location
    Xi´an
  • Type

    conf

  • DOI
    10.1109/INCoS.2013.21
  • Filename
    6630291