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A social networking site such as Facebook, Twitter, and Linked In generates a terabyte of data. The Frequent Itemset Mining (FIM) is most well known technique to extract knowledge from data. Mining terabytes of data using Frequent Itemset Mining technique on a single computer is not efficient. MapReduce framework is used for mining such large data in a parallel manner. MRApriori, IMRApriori, BigFIM,...
Privacy preserving data mining (PPDM) is a novel research area to preserve privacy for sensitive knowledge from disclosure. Many of the researchers in this area have recently made effort to preserve privacy for sensitive knowledge in statistical database. In this paper, we present a detailed overview and classification of approaches which have been applied to knowledge hiding in context of association...
Now-a-days it is common to share data between two organizations in many application areas. When data are to be shared between parties, there could be some sensitive patterns which should not be disclosed to the other parties. We address such the problem of sensitive classification rule hiding. We propose a blocking based approach for sensitive classification rule hiding. First we find the supporting...
Privacy preserving data mining (PPDM) is a novel research direction to preserve privacy for sensitive knowledge from disclosure. Many of the researchers in this area have recently made effort to preserve privacy for sensitive association rules in statistical database. In this paper, we propose a heuristic algorithm named DSRRC (Decrease Support of R.H.S. item of Rule Clusters), which provides privacy...
Information is valuable asset of any organization which is stored in databases. Data in such databases may contain credit card numbers, social security number or personal medical records etc. Failing to protect these databases from intrusions will result in loss of customer's confidence and might even result in lawsuits. Traditional database security mechanism does not design to detect anomalous behavior...
Data mining is the discovery of knowledge and useful information from the data stored in large databases. The classification of large data sets is an important problem in data mining. Most data mining algorithms cannot be applied to complex object databases unless it is converted into a single flat table. Much valuable information especially the linkages between objects could be lost by conversion...
Recent advances in cellular mobile communications have touched every aspect of our lives. In mobile computing, mobile hosts or mobile terminals (MTs) move randomly from one place to another within a well-defined geographical area. To provide timely services to mobile users, a challenging task is to track the location of the mobile user effectively so that the connection establishment delay is low...
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