Association Rule Mining Using Geometric Progression

Data mining is a popular and promising field. Therefore, in view of the importance of data mining, nowadays many types of research work are being done on data mining. Among the many popular techniques of data mining, one of the important and popular techniques is Association Rule Mining. There are many types of research work going on continuously in the field of association rule mining and for this many types of algorithms are used. Some of these important algorithms are the Apriori Algorithm, ECLAT Algorithm, and FP-Growth Algorithm. An attempt has been made to understand the workings of the Apriori Algorithm, ECLAT Algorithm, and FP-Growth Algorithm by continuous study. This attempt is to understand the capabilities and limitations of the Apriori Algorithm, ECLAT Algorithm, and FP-Growth Algorithm through the study. To minimize their drawbacks and to give a new direction to research, a new algorithm is proposed. The proposed algorithm works on a new type of technology. This new technology is based on the principles of Geometric Progression and works accordingly which may prove to be more suitable for Association Rule Mining.