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Privacy is an important issue in data mining and knowledge discovery. In this paper, we use the randomized response technology to conduct association rule mining. We propose a privacy preserving association rule mining algorithm which is called DDIL based on data disturbance and inquiry limitation. Applying DDIL on the data set, the original data can be disturbed and hidden and the degree of privacy-preserving...
Outlier detection is a hot topic of data mining. After studying the existing classical algorithms of detecting outliers, this paper proposes an outlier mining algorithm based on probability, and makes a new definition for outlier. It clusterings firstly with density-based algorithm, and determines suspicious outlier. Then, outlier will be detected according to probability. The experiment results on...
Many years of information progress makes organization or institute has different kinds of OLTP systems which are running under heterogeneous environment. And these OLTP systems accumulate lots of historical data. In order to provide effective global information for decision makers, global OLTP plays a crucial role. But, traditional method demands spending expensive to integrate the data in distributed...
Association rules mining is one of the most important and fundamental problems in data mining. Recently, in need of security, more and more people are studying privacy- preserving association rules mining in distributed database. This paper addresses a secure mining algorithm of association rules, which builds a globe hash table to prune item-sets and incorporate cryptographic techniques to minimize...
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