Exploratory data mining lead by text mining using a novel high dimensional clustering algorithm

被引：0

作者：

Amarasiri, R ^{[1
]}

Ceddia, J ^{[1
]}

Alahakoon, D ^{[1
]}

机构：

[1] Monash Univ, Sch Business Syst, Clayton, Vic 3168, Australia

来源：

ICMLA 2005: FOURTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, PROCEEDINGS | 2005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：

Text mining has emerged as a different stream in data mining because of the unstructured nature associated with free text. Many algorithms have been developed to assist in text mining. This paper presents the use of text mining based on a novel high dimensional clustering algorithm that leads to the exploratory data mining on data associated with the text. Experimental results of analyzing a real-world If text data set and associated data are also presented.

引用

页码：267 / 272

页数：6

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