南京林业大学学报(自然科学版) ›› 2003, Vol. 27 ›› Issue (03): 79-83.doi: 10.3969/j.jssn.1000-2006.2003.03.020

• 研究论文 • 上一篇    下一篇

现代信息数据的挖掘与发展

业宁;董逸生;张爱珍   

  1. 南京林业大学;江苏 南京 210037,东南大学,江苏 南京 210096;东南大学;江苏 南京 210096;南京林业大学;江苏 南京 210037
  • 出版日期:2003-06-18 发布日期:2003-06-18

Knowledge Discovery in Modern Information Data and its Advance

YE Ning1,2, DONG Yisheng2,ZHANG Aizhen1   

  1. 1.Nanjing Forestry University,Nanjing 210037,China;2.Southeast University,Nanjing 210096,China
  • Online:2003-06-18 Published:2003-06-18

摘要: <正>数据挖掘作为一项从海量数据中提取知识的新技术引起学术界和产业界的极大重视。笔者概括了数据挖掘的几种常见模式,如依赖模式、层次模式、序列模式等,并对这几种数据挖掘模式的特点进行了比较;阐述了从数据中提取知识的几种挖掘算法,如决策树、神经网络方法、遗传算法等;展望了数据挖掘模式和挖掘算法的发展趋势。

Abstract: Data Mining which discovers knowledge from massive data sets has been recognized by researchers and the industries.In this paper,several data mining patterns such as association pattern,arrangement pattern and serial pattern are generalized and the characteristics of these data mining patterns are compared.Further,several data mining algorithms such as decision trees,nerve network,genetic algorithm are introduced.Finally,a prospective of data mining pattern and data mining algorithm are proposed.

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