Association Rule Classification based on Multi-Dimensional Data Cubes

Abstract

Data mining facilitates the discovery of unrevealed trends from huge datasets. Data warehouse is a key technology for complex data analysis automatic knowledge extraction and decision making. Multi-dimensional database permits the data for efficient and appropriate storage. The dimensional table holds all different attributes and dimensions. Detecting the hidden association between the items are limited in OLAP. Researchers have proposed many ideas to reduce the limitations. This paper presents an approach called Association rule classification for Multi-Dimensional dataset. This proposed work detects the hidden association form OLAP and also categorize the rule sets effectively.