重点综述了基于局部信息的全局数据挖掘方法。根据数据挖掘的过程,将该问题的研究划分成三个阶段,即利用粒度数据表示进行挖掘、利用局部信息改善全局挖掘的效率和利用局部模式结果获得全局数据理解,并对每个阶段进行了分类论述。最后总结了全文并指明了未来的研究方向。
This paper investigated data mining through combining global model constructing and local pattern mining, especially studied global data mining based on local information. On the basis of the process of data mining, it divided this problem into three phases, including improving the efficiency of mining using granular representation, improving the interpretation of local mining using global model, improving the efficiency and accuracy of global mining. And the paper reviewed these three problems respectively. Finally, the paper summarized and also pointed out some future works.