@inproceedings{edf83ac2558a44ccbdf9647dc4cf90c6,
title = "CBCM: A cell-based clustering method for data mining applications",
abstract = "Data mining applications have recently required a large amount of high-dimensional data. However, most clustering methods for the data miming applications do not work efficiently for dealing with large, high-dimensional data because of the so-called {\textquoteleft}curse of dimensionality{\textquoteright} and the limitation of available memory. In this paper, we propose a new cell-based clustering method (CBCM) which is more efficient for large, high-dimensional data than the existing clustering methods. Our CBCM provides an efficient cell creation algorithm using a space-partitioning technique and uses a filtering-based index structure using an approximation technique. In addition, we compare the performance of our CBCM with the CLIQUE method in terms of cluster construction time, precision, and retrieval time.",
author = "Chang, \{Jae Woo\}",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2002.; 3rd International Conference on Advances in Web-Age Information Management, WAIM 2002 ; Conference date: 11-08-2002 Through 13-08-2002",
year = "2002",
doi = "10.1007/3-540-45703-8\_27",
language = "English",
isbn = "9783540440451",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "291--302",
editor = "Xiaofeng Meng and Jianwen Su and Yujun Wang",
booktitle = "Advances in Web-Age Information Management - 3rd International Conference, WAIM 2002, Proceedings",
}