Association Rule Mining Algorithms

Knowledge is strength. With the rapid development of information technology, the development of e-commerce and the development of WWW applications, massive amounts of data have been continuously collected in the databases of many application areas, which contain much useful patterns, and it is very important to find the hidden and previously unknown i nformation for these areas, data mining aims at the tasks of the above work. In recent years, some new concepts and theories of data mining have been proposed, and many data mining products are also presented by some world Important IT companies(such as IBM, Oracle and Microsoft, etc.).Association rule mining is a form of data mining to discover previously unknown, interesting relationships among attributes from large databases. Due to its simple form and being easily understood, association rule mining has attracted great attention in database, artificial intelligent and statistics communities, and a lot achievements have been made in its study. Compared with artificial method, such as neural network, genetic algorithm and statistics, it can process larger dataset, on the other hand, artificial method usually processes a small set of data, and it aims at finding a model between inputs and outputs. Association rule mining can find large number of patterns among attributes. Furthermore, although large datasets can be processed in statistics, these work aims at finding data distributions or statistical model.Association rules has attracted much attention from practitioners and researchers since it was introduced by Agrawal in 1993, and several algorithms have been developed to cope with the popular and computationally expensive task of association rule mining, such as sampling algorithm, parallel algorithm, etc. But there are many difficulties, for example, how can the user obtain the precise and efficient results instantly when mining the continuously updated data? And the user has to preset fixed mining parameters, it will cost much time and generate many redundant rules if the parameters are not suitable. So it need not only design the efficient algorithms to mining association rules, but also cry for the efficient algorithms to update, maintain and manage the discovered association rules.Supported by the NSF of GanSu, this dissertation mainly focuses on some key problems, including the algorithm of maintaining the discovered association rules, the algorithm based on Galois(concept) lattices. Some new definitions, theorems and algorithms are presented and tested, and some problems in both theory and practical applications are solved successfully.