Algorithm of mining fuzzy association rules in network management

This paper discusses the current status of the research about mining association rules in a database, which points out the shortcoming of classical a priori´s algorithm, and presents some theorems of mining association rules based on reducing records in a larger database. It also applies the theory of fuzzy sets to processing fuzzy data of traps in a network management. According to those theorems and the theory of fuzzy sets, we have designed the AprioriFuzzy algorithm to mine fuzzy association rules in database. Through the performance of AprioriFuzzy algorithm is analyzed and evaluated in this paper, this algorithm can save mining time about 30% and can mine fuzzy association rules in fuzzy data effectively. It has been implemented on PC in Visual C++6.0 and has been applied to mine the trap´s information in the network management based on SNMP protocol.