数据挖掘研究现状及发展趋势

基金项目:

甘肃省教育厅科研项目(0903-07)，国家自然科学基金项目(50967001)

详细信息

Existing Situation of Data Mining Research and Its Development Tendency

College of Electrical and Information Engineering of Lanzhou University of Technology, Lanzhou 730050, China. 2.Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou 730050, Chi

摘要: 从数据挖掘的定义出发，介绍了数据挖掘的神经网络法、决策树法、遗传算法、粗糙集法、模糊集法和关联规则法等概念及其各自的优缺点；详细总结了国内外数据挖掘的研究现状及研究热点，指出了数据挖掘的发展趋势。
- 数据挖掘 /
- 挖掘算法 /
- 神经网络 /
- 决策树 /
- 粗糙集 /
- 模糊集 /
- 研究现状 /
- 发展趋势
Abstract: From the definition of data mining, the paper introduced concepts and advantages and disadvantages of neural network algorithm, decision tree algorithm, genetic algorithm, rough set method, fuzzy set method and association rule method of data mining, summarized domestic and international research situation and focus of data mining in details, and pointed out the development trend of data mining.
- data mining, algorithm of data mining, neural network, decision tree, rough set, fuzzy set, research situation, development tendency