An Intelligent Association Rule Mining Model for Multidimensional Data Representation and Modeling

[1] Using the new data mining techniques it can be discovered new patterns that offer new path analysis, new association rules, and new classification and clusters rules.. As we

In tradition approach association rule mining and probabilistic models are commonly used. Models like sequential modeling are effective in the recommendation [2]. Markov

This problem used to mine frequent patterns from the databases like Retail transaction database, Chess database and Mushroom database using association mining

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