A Rule based Data Mining Mechanism: Association Rule Mining

For many years, statistics have been used to analyze data in an effort to find correlations, patterns, and dependencies. However, with advancement in technology, more and more data are available, which greatly exceed the human capacity to manually analyze them. Knowledge discovery in financial organization have been built to evaluate their operation and mainly to support decision making using knowledge as key factor; Before the 1990’s, data collected by bankers, credit card companies, department stores and so on have little used. But in recent years, the idea of data mining has emerged with the increase in computational power. Today data mining is primarily used by companies with a strong consumer focus-retail, financial, communication, medical, agriculture and marketing organizations. In this paper, we investigate the use of various data mining techniques for knowledge discovery in agriculture sector. Existing software are inefficient in showing such data characteristics. We introduce different exhibits for discovering knowledge in the form of association rules. Proposed data mining techniques, the decision maker can define the expansion of agriculture activities to empower the different forces in existing agriculture sector. This paper is an outcome of the study on data mining from exiting literature.