Finding Association Rules through Efficient Knowledge Management Technique

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

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

In this paper we propose a new approach based on Particle Swarm Optimization Algorithm to mine association rules for both frequent and infrequent itemsets in an efficient way.

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

In this research, association rule mining is used to analyze technology integration and diversification in a firm level.. Data mining, which is referred to as

The courses association rules, generated in Step III, are used to recommend elective courses. This step is the core step in our recommendation system. The recommendation

The ACDR algorithm consists of 5 main steps which are (1) finding association rules, (2) clustering target association rules and general association rules into two groups

This algorithm can extract the minimal generators and build a structure partially ordered called Frequent minimal generators lattice in order to perform a v ertical