Discover And Study Securities Association Rules In Multidimensional Database On Statistics

Association rules is an effective method for describing the dependency relations in data, and it is one of the improtant aspects of knowledge discovery. Taditional association rule mining methods lack of focus on the results, and the procedure is slow. Those algorithms express the regularities with low level primitive data, and the mining association reules are difficult to understand. Furthermore, the desirable knowledge must be filtered out from huge results in a post-processing step.Additionaly, with data quantity expanding rapidly, the structure of database is becoming more and more complicated. Some of these factors are related with client 's due data structure and others has nothing to do with them.Data mining is on the interface of Computer Science and Statistics, utilizing advances in both disciplines to make progress in extracting information from large databases. This article highlights some statistical themes that are directly relevant to data mining . A method based on statistics and professional experiment is introduced in this paper aims to reduce factors which hardly affect result .