J4 ›› 2013, Vol. 48 ›› Issue (7): 72-78.

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Research on spam identification based on social computing and machine learning

DONG Yuan1, XU Ya-bin1,2*, LI Zhuo1,2, LI Yan-ping1   

  1. 1. School of Computer, Beijing Information Science &Technology University, Beijing 100101, China;
    2. Beijing Key Laboratory of Internet Culture and Digital Dissemination Research,
    Beijing Information Science &Technology University, Beijing 100101, China
  • Received:2013-06-17 Published:2013-12-03

Abstract:

Based on the investigation and analysis of the current various spam recognition methods, a new spam identification method is proposed inspiring by social computing theory and methods of machine learning. Firstly, initial recognition of spams is taken using a relationship map of the interactions among contacts, which is constructed with the help of the characteristics in the mail heads reflecting the social relation of contacts. After that, for the mails of the contacts which are not able to be identified having social relation, recognition methods based on machine learning are taken. Through the experiments, it is demonstrated that the proposed method can identify spams more accurately while taking a shorter time, comparing with the ones based on Na-ve Bayes.

Key words: social computing; spam identification; social relations; machine learning

CLC Number: 

  • TP393
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