为了适应真实环境中数据量大、流程复杂、计算密集的数据挖掘需求,为提高关联规则增量更新挖掘效率,改变已有算法的串行执行方式,提出了一种基于云计算模型的关联规则增量更新方法,以解决海量数据挖掘问题。介绍了云计算相关概念、模型与执行流程等,提出一种单节点环境下的关联规则增量更新算法IUM (incremental updating mining),基于云计算模型设计新的关联规则增量更新算法 CIUM (cloud incremental updating mining)完成增量挖掘工作。实验结果表明,并行算法有效可行,具有高效性与良好的扩展率,能够有效针对海量数据进行更新挖掘。
To deal with the problem in true environment caused by data mining tasks with larger amount of data, complex pro- cessing and intensive computing, to improve the association rules incremental updating mining efficiency, to change the existing algorithm of serial implementation methods, and to solve mass data mining problems, an association rules incremental updating method is proposed on the basis of cloud computing. Firstly, concepts concerning cloud computing, the cloud model and operm ring process and so on are introduced. Then, a new association rules incremental updating mining algorithm (IUM) is proposed. Lastly, new association rules incremental updating mining algorithm (CIUM) is designed on the basis of cloud platform. After large number of experiments, the results show that the paralleled algorithm is feasible, highly efficient, expandable, and the al- gorithm can mining mass data effectively.