Knowledge Discovery for Supply Chain Management Systems: a Schema Composition Approach

Decision support and global knowledge discovery on SCM system have become an important issue, since SCM has become a common way for achieving competitive advantage. This research proposes a distributed data mining mechanism that uses a relationship metadata to integrate the data source derived from partner of the supply chain, thus solving the problem of excessive and various data volume in the current supply chain. With prior relevance detection, the mining process will be much better. On the other hand, since data provided by the partner is not extremely complete for traditional data mining, we can utilize peculiarity oriented data mining process to generate the rules across the organizations in order to achieve more competitive advantage. Therefore, all important rules will be mined successfully in our architecture. The results provided by the experimental system can identify the relevant resource effectively with more user-defined requirements.