Information mining with semi-supervised learning

被引：0

作者：

Klose, A ^{[1
]}

Kruse, R ^{[1
]}

机构：

[1] Otto Von Guericke Univ, Dept Comp Sci, Magdeburg, Germany

来源：

SOFT METHODOLOGY AND RANDOM INFORMATION SYSTEMS | 2004年

关键词：

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：

The challenge of analyzing huge amounts of data is usually known as Data Mining, and a number of methods has been proposed for that purpose. However, the application areas and thus the characteristics of the data are changing. More complex and heterogeneous data call for more sophisticated algorithms. In this paper we present some of the current trends and challenges. We illustrate, why we expect an increasing interest in semi-supervised methods, especially in combination with fuzzy techniques.

引用

页码：67 / 74

页数：8

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