Intelligent data analysis: Issues and challenges

被引:0
|
作者
Nayak, R [1 ]
机构
[1] Queensland Univ Technol, Sch Informat Syst, Brisbane, Qld 4001, Australia
关键词
data analysis; data mining; risk asseszrnent of level crossing; rule extraction; neural networks; rule induction;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Today with the advances of technology, mountainous amounts of data are now available in science, business, industry and many other areas. Evaluation of these collected data may lead to the discovery of trends and patterns hidden within the data that increase the working efficiency and improve the quality of decision making. Of course this advantage comes with a price. It is becoming more and more difficult to gain some valuable information when analysing with these increasing data sets. This paper attempts to discuss a wide range of problems that may appear while analysing the data, and suggests strategies to deal with them. Sonic of these problems and suggestions are examined with the results of data analysis on a real-life example of risk assessment of level crossing data.
引用
收藏
页码:400 / 405
页数:6
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