摘要
随着大型数据库的不断涌现,如何从浩如烟海的数据中发现隐藏的有用知识,成为一个迫切需要研究的课题。因此,知识发现和数据挖掘应运而生。该文提出了数据挖掘的基本概念,数据挖掘是数据库技术、人工智能、机器学习、统计分析、模糊逻辑、模式识别和人工神经网络等多个学科相结合的产物,然后分析了数据挖掘一般算法的结构,并且对数据挖掘技术进行了详细分类,主要包括决策树技术、神经网络技术、粗集以及模糊集等十多项挖掘技术。最后讨论了数据挖掘在人工智能、电子商务应用和移动通信计算等方面的研究方向。
With rapid emerging of large databases, how to discover the useful information and knowledge quickly and exactly, has become a key research topic. So, knowledge discovery and data mining are proposed with a new study field developed. The article proposes a new concept of data mining, it is the main step in KDD process and draws upon many techniques from diverse fields, such as database technology, artificial intelligence, machine learning, statistics, fuzzy logic, pattern recognition, and artificial neural network, etc. Then,it analyses the frame of general algorithm about data mining and gives a detailed classification of these technologies. They mainly contain technologies of decision rule trees, neural network, rough set and fuzzy sets, etc. Finally, this paper discusses the primary research area of data mining, such as artificial intelligence, ebusiness, mobile computation.
出处
《计算机仿真》
CSCD
2005年第10期1-3,共3页
Computer Simulation
关键词
数据挖掘
决策树
神经网络
数据库
Data mining
Decision trees
Neural network
Database
作者简介
王斌（1982.10-）,男（汉族）,河北省衡水市人,学士,主要研究方向：道路与桥梁.
