@article{ART000931753},
author={Shin-Won Lee and An Dong Un and Chung Seong Jong},
title={Selection of Cluster Hierarchy Depth and Initial Centroids in Hierarchical Clustering using K-Means Algorithm},
journal={Journal of the Korean Society for Information Management},
issn={1013-0799},
year={2004},
volume={21},
number={4},
pages={173-186},
doi={10.3743/KOSIM.2004.21.4.173}
TY - JOUR
AU - Shin-Won Lee
AU - An Dong Un
AU - Chung Seong Jong
TI - Selection of Cluster Hierarchy Depth and Initial Centroids in Hierarchical Clustering using K-Means Algorithm
JO - Journal of the Korean Society for Information Management
PY - 2004
VL - 21
IS - 4
PB - 한국정보관리학회
SP - 173
EP - 186
SN - 1013-0799
AB - Fast and high-quality document clustering algorithms play an important role in providing data exploration by organizing large amounts of information into a small number of meaningful clusters. Many papers have shown that the hierarchical clustering method takes good-performance, but is limited because of its quadratic time complexity. In contrast, with a large number of variables, K-means has a time complexity that is linear in the number of documents, but is thought to produce inferior clusters. In this paper, Condor system using K-Means algorithm Compares with regular method that the initial centroids have been established in advance, our method performance has been improved a lot.
KW - 문서 클러스터링;K-Means 알고리즘;클러스터 계층 깊이;클러스터 초기값;계층적 클러스터링;클러스터 중심document clustering;K-Means algorithm;cluster hierarchy depth;cluster initial value;hierarchical clustering;cluster centroid
DO - 10.3743/KOSIM.2004.21.4.173
ER -
Shin-Won Lee, An Dong Un and Chung Seong Jong. (2004). Selection of Cluster Hierarchy Depth and Initial Centroids in Hierarchical Clustering using K-Means Algorithm. Journal of the Korean Society for Information Management, 21(4), 173-186.
Shin-Won Lee, An Dong Un and Chung Seong Jong. 2004, "Selection of Cluster Hierarchy Depth and Initial Centroids in Hierarchical Clustering using K-Means Algorithm", Journal of the Korean Society for Information Management, vol.21, no.4 pp.173-186. Available from: doi:10.3743/KOSIM.2004.21.4.173
Shin-Won Lee, An Dong Un, Chung Seong Jong "Selection of Cluster Hierarchy Depth and Initial Centroids in Hierarchical Clustering using K-Means Algorithm" Journal of the Korean Society for Information Management 21.4 pp.173-186 (2004) : 173.
Shin-Won Lee, An Dong Un, Chung Seong Jong. Selection of Cluster Hierarchy Depth and Initial Centroids in Hierarchical Clustering using K-Means Algorithm. 2004; 21(4), 173-186. Available from: doi:10.3743/KOSIM.2004.21.4.173
Shin-Won Lee, An Dong Un and Chung Seong Jong. "Selection of Cluster Hierarchy Depth and Initial Centroids in Hierarchical Clustering using K-Means Algorithm" Journal of the Korean Society for Information Management 21, no.4 (2004) : 173-186.doi: 10.3743/KOSIM.2004.21.4.173
Shin-Won Lee; An Dong Un; Chung Seong Jong. Selection of Cluster Hierarchy Depth and Initial Centroids in Hierarchical Clustering using K-Means Algorithm. Journal of the Korean Society for Information Management, 21(4), 173-186. doi: 10.3743/KOSIM.2004.21.4.173
Shin-Won Lee; An Dong Un; Chung Seong Jong. Selection of Cluster Hierarchy Depth and Initial Centroids in Hierarchical Clustering using K-Means Algorithm. Journal of the Korean Society for Information Management. 2004; 21(4) 173-186. doi: 10.3743/KOSIM.2004.21.4.173
Shin-Won Lee, An Dong Un, Chung Seong Jong. Selection of Cluster Hierarchy Depth and Initial Centroids in Hierarchical Clustering using K-Means Algorithm. 2004; 21(4), 173-186. Available from: doi:10.3743/KOSIM.2004.21.4.173
Shin-Won Lee, An Dong Un and Chung Seong Jong. "Selection of Cluster Hierarchy Depth and Initial Centroids in Hierarchical Clustering using K-Means Algorithm" Journal of the Korean Society for Information Management 21, no.4 (2004) : 173-186.doi: 10.3743/KOSIM.2004.21.4.173
