Research On The Techniques Of Association Rule Mining

With the development of database and Internet technology, the volumes of data and information which can be obtained increase at tbe speed of exponent. Data mining comes up to solve the problem that how to distill the useful knowledge which can be used for decision supporting from masses of data. Association rule is a simple statement about the cooccurrence probability of some certain events in database. Association rule mining aimed to find the associated relationship of a great deal of item sets in the database. At present, association rule mining has become an important branch of data mining research.This thesis emphasizes on several techniques of association rule mining. At first, the background knowledge of data mining and association rule mining are introduced briefly. After that, some kinds of common used association rule mining algorithms are discussed respectively; among them certain typical algorithms are analyzed and compared thoroughly. Furthermore, the results visualization techniques of association rule mining are studied. The followed content is the discussing of privacy preserving techniques. Then, this thesis presents an improved algorithm based on classic Apriori algorithm, and extends it for class association rule mining. In the last part of the thesis, we give the conclusion and prospect of data mining research.