Title :
Exploratory data mining lead by text mining using a novel high dimensional clustering algorithm
Author :
Amarasiri, Rasika ; Ceddia, Jason ; Alahakoon, Damminda
Author_Institution :
Sch. of Bus. Syst., Monash Univ., Victoria, Vic., Australia
Abstract :
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 text data set and associated data are also presented.
Keywords :
data mining; pattern clustering; text analysis; data mining; high dimensional clustering; text mining; Clustering algorithms; Data analysis; Data mining; Databases; Frequency conversion; Information retrieval; Machine learning algorithms; Organizing; Software algorithms; Text mining;
Conference_Titel :
Machine Learning and Applications, 2005. Proceedings. Fourth International Conference on
Print_ISBN :
0-7695-2495-8
DOI :
10.1109/ICMLA.2005.29