DATA CUBE – BASED IN QUANTITATIVE MULTIDIMENSIONAL ASSOCIATION RULES FROM AGRICULTURAL DATA WAREHOUSE

K.Rani; K. Renuga Devi; S. Irudhaya Ananthi

Article Information

Published In Volume 2, Issue 1 (2016)
Publication Date July 23, 2026
Manuscript ID IJCRCST-JANUARY16-14
Article Type Research Paper
Pages 442 - 447
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Abstract

In India Agriculture play a major role. Agriculture data is highly broadened in terms of irrigation sources, climate, soil and inputs like fertilizers and pesticides. For sustainable growth of agriculture, these resources need to be monitored, analyzed and allocated optimally. Data mining techniques may be used in agricultural data for mining the association rules among various inputs and outputs used for cropping. This paper is making an effort to study the existing data mining algorithms to mine association rules widely used in corporate sector. The paper also presents an idea for mining quantitative multidimensional association rules from Agricultural Data Warehouse based on concise data using data cubes.

Keywords

Data mining KDD Association rule Multi dimensional data Data cube Quantitative Association Rules Agricultural data warehouse.

Authors

K.Rani

K. Renuga Devi

S. Irudhaya Ananthi

How to Cite this Article

K.Rani, K. Renuga Devi, S. Irudhaya Ananthi (2016). "DATA CUBE – BASED IN QUANTITATIVE MULTIDIMENSIONAL ASSOCIATION RULES FROM AGRICULTURAL DATA WAREHOUSE". International Journal of Contemporary Research in Computer Science and Technology, 2(1), pp. 442-447.