HIDING SENSITIVE ASSOCIATION RULE USING HEURISTIC APPROACH

Sensitive rules are those rules the database owner is trying to hide using privacy preserving algorithms in data mining, and non-sensitive rules are useful rules

All association rule mining algorithms like apriori algorithm and fp-growth algorithms are using mainly two steps in extracting the association rule. 1) Generation of

Generation of association rule was first introduced in [18] and AIS algorithm was proposed for mining of all types of association rules. An algorithm called SETM was proposed

Thus the main aim of this research is to perform association rule from multiple heterogeneous data sources using multi agent system and then unifying the result to knowledge base

After studying the algorithm on Association Rule Mining using the APRIORI technique, it has been analyzed that this technique is useful for only small datasets ,on

Our research is a further step of the Tree Based Association Rule Mining (TBAR) algorithm, used in relational databases for finding the association rules .In

The most interesting one is that oscillating search algorithm which is used for feature selection provides the best optimal features and no where it is applied or used for

The work on association rules was extended from patterns [1,2,11] ,the authors explored data cube-based [2] rule mining algorithms on multidimensional databases, where