IMPROVING PERFORMANCE OF APRIORI ALGORITHM USING HADOOP

Ravindra Bachate, Hyder Ali Hingoliwala

Abstract: Spatial data is a data having a geological information. This paper explores the use of Hadoop framework to improve the performance of Apriori algorithm for spatial data mining. FP growth algorithm is better than Apriori but it fails in certain situations. By applying the Apriori algorithm parallely using Hadoop framework to spatial data, we can perform well as compare to FP growth. This paper includes clustering based on geological location, classification based on mineral resource type and spatial coherence between mineral resources. Spatial data mining find out the different association rules by observing the spatial data by using Apriori algorithm. The result of the paper will indicate the accurate prediction of occurrence of commodity with respect to other commodity of mineral resources.

Keywords: Hadoop, data mining, association rules, clustering, spatial coherence

DOI: https://doi.org/10.15623/ijret.2014.0312038