ANALYSIS METHODS OF WORKFLOW EXECUTION FOR DATA BASED ON ROUGH SET THEORY IN DATA MINING

Exploring the trivial workflow data needs high performance data processing technology. In this research work we put forward analysis method of workflow execution data based on data mining. The main idea of it is to retrieve the workflow data to a data warehouse and adopt OLAP technology and data mining method to support customers to select different measures and view the corresponding data in different dimensions and different abstract levels, which is important for them to make decision. This research work presents the use of a relatively new method, the Rough Set (RS) theory for knowledge acquisition in time sequence condition monitoring. An additional attraction of the RS theory is that it allows automated generation of knowledge models, offering clear explanations to the inferences performed in diagnosis.