Intelligent Analysis And Privacy-Protection Of Mobile Data

Smart phones, mobile commerce has become increasingly popular, Associated with all aspects of our lives. Not only that, Pocket PC, IPAD and other mobile devices have to let us anytime and anywhere communicate with others browse the web, stock trading, payment, etc. It is Function of hard to break away.China's mobile phone users over 700 million, Obviously, compared to the computer, mobile phone penetration rate is much higher than the computer. In the third mobile commerce, as mobile operators, need to be more secure, more accurate business promotion marketing and personalized recommendations. How to do this, in the face in front of a large number of mobile data, its need a lot more scientific data mining and intelligence analysis and privacy-protection Although privacy preserving data mining has become increasingly concerned about the object, but at home and abroad study, the combination of real data privacy protection of data mining is still relatively rare. The article is based on Rakesh Agrawal perturbation theory of privacy protection, the use of mobile data in the intelligent analysis needed to come to mining-related knowledge, Main content:First, In this paper, we have data mining and privacy protection based on the theory of intelligent mobile data analysis related discussions.Secondly, Secondly, a large number of original mobile data to make business understanding, data preprocessing, and to construct a decision tree model base on customer call to remind, the relevance of mobile business model recommended,and Mobile customer segmentation of the cluster model. Have been effective business conclusions.Finally, will be the Agrawal privacy protection algorithm applied to the three models, Various factors have been the relationship between, Qualitative analysis of the relationships, An example of the hypothetical model verification and correction, Building privacy protection based on data mining models.The results show that:Through quantitative analysis and qualitative analysis of the original model and privacy models were compared, the differences remain within the controllable range, and compare the two models in the mobile business can play in both the desired results. Therefore, the privacy protection in mobile commerce, Not a good solution to privacy issues, and can well use the same move in the real business issues...