The Research Of Mining Association Rules On Information System

Computer network and database technology development needs, access to knowledge in the database and data mining techniques has become a very popular area of research in artificial intelligence and machine learning process. KDD technology is primarily used to discover hidden in information system, potential knowledge is in fact looking for data validation rules and patterns in the data collection. In many KDD, association rules are subject to widespread concern in the research field.The purpose of the association rules from information systems in order to find interesting associations between items and the correlation between its application context has expanded to include network optimization, intrusion, analysis from a simple online shopping and DNA sequence analysis, software testing equipment diagnosis and other applications on the domain. Theoretical research content mining frequent patterns from the initial excavation extended to the closed mode, the maximum pattern mining, incremental mining topic interest measure of privacy protection, data streaming and other types of data on the association rule mining. Therefore it is necessary to research and explore the different information systems, data association rules.In this paper, the existing rules of the association of technology and research directions, the corresponding solution, and got some innovative results. The main work in the following areas:The first chapter introduces data mining, background and status of rough set theory, and association rules the reality of the concept and research and direction;The second chapter describes the basic concepts of information systems, information tables and decision-making table, as well as incompatible with the judgment;Chapter3this chapter discusses the data pre-processing methods for information systems, mainly from incomplete data processing, discrete property values to discuss the deal with two aspects;Chapter4this chapter introduces the concept of gray theory, gray theory clustering method to the process of decision-making table constructed from the information table;Chapter5This chapter describes several commonly used association rules, and proposed a set of association rules algorithm based on the coverage object;Chapter6This chapter describes the association rules reduction method, by association rules reduction, has been excavated out of the rules, delete, merge and other operations, resulting in good generalization ability, covering the targets of rules.In practical problems, many information systems due to noise, incomplete information, result in system inconsistent. The study would therefore like to obtain a valid association rules from the original information system is very significant issue. In the end, users need a more concise, more generally, the more reliable association rules.