Research And Application Of Quantitative Association Rules Mining

Association Rules Mining is an important sub-branche of data mining. It has wide range of applications from the initial retail trade to the finance and insurance industry,IT industry and so on. The quantitative association rules mining is an important research direction of association rules mining,which is one of the key technologies to solve knowledge discovery in relational database.This paper summarizes the background and causes,the technology methods and the developing trend of data mining, then presents association rules about its concept and sorts and steps for mining the data,The emphasise is quantitative association rule. Based on the analysis of the classical apriori algorithm and its improved algorithms, the paper tries to study mining algorithm based on boolean matrices, puts forward some suggestions for improvement and finaly realizes them. Upon the above research, the meteorological data can be mined by the improved algorithm of association rules,and the resulets are applied to weather forecast. These are realized under the environment of lab and the experimental results are analyzed which will lay foundations for the researches in future.The exploding data was brought by meteorological information, and the hidden and unknown information is behind these data. We use different mining methods under different conditions in order to get this information. In short, the meteorological data acquisition, processing and application processes using data mining theory and technology can discover the intrinsic relations or patterns and do a better job of forecasting weather efficiently, provide better service for the proper making-decision.