一种关系型数据库并行概念学习系统的探讨

关系型数据库中包含了大量的关系模式,其中的数据结构一般为结构化或半结构化数据。通过机器的概念学习,从这些数据结构中提取信息、得到更高层次的概念,这个机器学习的过程效率高低,将直接影响概念的获取,建立一个并行概念学习系统是一种比较可行的方法。文中探讨了关系型数据库的并行概念学习方法,给出了一种并行学习策略,建立了一种并行概念学习系统,可以有效地提高关系型数据库概念学习的效率,从而挖掘出更高层次的概念。

Research on Parallel Concept Learning System Based on Relational Database

In relational database,there are massive relational patterns,in which,data structure is generally structured data or semi-structured data.Through machine concept learning,information of these data structure was abstracted,and more pro- found concepts were obtained.The efficiencyof this machine learning process will directly affect the gaining of concepts.Thus, establishing a parallel concept learning system is a feasible method.In the article,the parallel concept learning method of rela- tional database has been discussed,one kind of parallel study strategy has been put forward and one parallel concept learning system has been setup so as to effectively enhance the efficiency ofthe concept learning of relational database,and more profound concepts will thus be developed.