Association Rule Mining Using k-Map Model in Data Mining

In data mining, many algorithms were suggested to define the frequent rules within the data set. One of the problems is to choose a correct algorithm for the problem and the determination of the efficiency of the algorithm has important role during the investigation of hidden knowledge. The thesis describes how to handle data set with Association Rules Analysis/ Market Basket Analysis with the popular Apriori algorithm and k -Map algorithm of data mining. The goal of this thesis is to find the most frequent patterns within the data set and then using different measurements to do further investigation on the obtained frequent patterns. Keywords: Data Mining, Association Rules Analysis, Market-Basket Analysis