Study and Analysis of Infrequent Behaviour Patterns in Business Process Event Logs

Data Mining consists of variety of techniques. Association rule mining is one of the familiar techniques used to solve many real world problems like market basket analysis, marketer prediction. The dynamic data mining is a new phenomenon used to handle event log information. It is highly used for business applications. The frequent item set mining with association rules gives better results with process log data. But least frequent items affect the performance rate of business transactions. In order reduce the noise and least significant items, filtering techniques are used. This paper is aimed to remove infrequent behavior from event logs.