The design of architecture, workflow, algorithm on grid system for Social Network context prediction analysis

In telecom social network, the context-based prediction analysis is an important topic, and computing of some context parameters using great amount of data is a problem so far. Architecture of DMG (data mining grid) is proposed and prototype of MDG is designed to solve the computing problem. Two of the important issues in DMG, which are the design of the workflow service in DMG and the distributed data mining algorithm, are investigated. Finally a sample application in telecom field customer churn context prediction analysis is investigated and illustrated. In the sample application, Centrals, which is computed by parallel algorithm on DMG, is an important measure in telecom social network. And it is an important context parameter proved by the experiment, which benefits to enhance the precise of context-based prediction of the customer churn in telecom social network.