Intelligent Decision Support System Based on Data Mining: Foreign Trading Case Study

In this paper, we propose an intelligent decision support system based on data mining (IDSSDM), which integrates several data mining techniques and considers both structured data and semi-structured data. For structured transactional data, online analytical processing (OLAP) is first used to access data warehouse for multidimensional analysis and primary decision support. To uncover hidden relationships among different attributes, KDD*, a software designed by us, is used for discovering association rules among massive trading data. As for semi-structured data, classification and clustering is exploited for contract documents mining; while Web usage mining is used for analyzing the behavior of the users in order to extract relationships in the recorded data. Furthermore, knowledge discovery in knowledge base (KDK) is used as the primary inference engine. As the main business intelligence tool, the system has been adopted by E-Commerce Center of Ministry of Commerce of the People´s Republic of China.