教育信息化、大数据战略已成为一种国家意志,通过数据挖掘发现新知识或更新现有知识是计算机信息处理最理想的产品之一。基于明确知识发现与数据挖掘(Knowledge Discovery and Data Mining,KDDM)的领域范畴,在回顾与综合分析欧美国家KDD...教育信息化、大数据战略已成为一种国家意志,通过数据挖掘发现新知识或更新现有知识是计算机信息处理最理想的产品之一。基于明确知识发现与数据挖掘(Knowledge Discovery and Data Mining,KDDM)的领域范畴,在回顾与综合分析欧美国家KDDM过程模型研究的基础之上,把KDDM过程模型概括为学科交叉性、应用多样性、本质探索性、过程迭代性、目标与结果不确定性等五个主要特征,从中获得在教育领域应用与实施KDDM工程实践的四点启示,并对KDDM在教育领域中的应用提出四点建议。展开更多
Information recording in paper is difficult to save, search or be used. It can be digitized only by mass production. This paper, introduces the methods of increasing efficiency and controlling quality in the productio...Information recording in paper is difficult to save, search or be used. It can be digitized only by mass production. This paper, introduces the methods of increasing efficiency and controlling quality in the production of Chinese Material Digitizing: reconstruct the new recognition system by twice classifying, using multi-recognition cores, multi-checking and modifying, inserting errors.展开更多
文摘教育信息化、大数据战略已成为一种国家意志,通过数据挖掘发现新知识或更新现有知识是计算机信息处理最理想的产品之一。基于明确知识发现与数据挖掘(Knowledge Discovery and Data Mining,KDDM)的领域范畴,在回顾与综合分析欧美国家KDDM过程模型研究的基础之上,把KDDM过程模型概括为学科交叉性、应用多样性、本质探索性、过程迭代性、目标与结果不确定性等五个主要特征,从中获得在教育领域应用与实施KDDM工程实践的四点启示,并对KDDM在教育领域中的应用提出四点建议。
文摘Information recording in paper is difficult to save, search or be used. It can be digitized only by mass production. This paper, introduces the methods of increasing efficiency and controlling quality in the production of Chinese Material Digitizing: reconstruct the new recognition system by twice classifying, using multi-recognition cores, multi-checking and modifying, inserting errors.
