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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...
To gain the competitive advantage in today's age of technology, growing data and to bear the competitive pressure, making strong decisions according to customer's need and market trend has become very important. With huge amount of data on internet, web data mining has become very significant. Web Usage helps companies to produce productive information pertaining to the future of their business function...
The main goal to extract knowledge in database is to help the user to give semantics of data and to optimize the information research. Unfortunately, this fundamental constraint is not taken into account by almost all the approaches for knowledge discovery. Indeed, these approaches generate a big number of rules that are not easily assimilated by the human brain. In this paper, we propose a new approach...
This paper presents an applied study in data mining and knowledge discovery. It aims at discovering patterns within historical students' academic and financial data at UST (University of Science and Technology) from the year 1993 to 2005 in order to contribute improving academic performance at UST. Results show that these rules concentrate on three main issues, students' academic achievements (successes...
This paper analyzed some problems existing in the business search engine when it searched the special fields, and then put forward a set of search engine scheme about data warehouse design based on data mining. It applied the improved association rules algorithm to text clustering algorithm. At the same time in combination with the advantages of J2EE architecture in system development, this paper...
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