Research Of Grid-based Distributed Association Rule Mining System Model And Algorithms

In many industrial, scientific and commercial applications, it is often necessary to analyze large sets, maintained over geographically distributed sites. The grid can play a significant role in providing an effective computational support for knowledge discovery applications. The author studied OGSA, analyzed presented Knowledge Grid (KG) infrastructure and semantic learning process based on KG., accordingly, built a distributed mining model with the service function based on KG and used UML to build active model for it.On the basis of KG, a Grid-based distributed and parallel association rule mining system model targeting a real-life application scenario typical in the business realm--franchise supermarket basket analysis is presented. The model designed on topof grid mechanisms provided by Globus, used the basic grid services such as communication, information, and resource management, and followed the idea of mining model based on KG, accordingly, implemented association rule mining model based on Grid for business application.. The model adopted two improved distributed data mining algorithms based on Apriori and Distributed FP-tree to build Grid-based parallel and distributed data mining. The two algorithms' designing considered distributed mining, resource sharing and service-oriented characteristics of grid. Finally, we analyzed, tested, and assessed the model and algorithms.