In this paper, we emphasize the need for data cleansing when clustering large-scale transaction databases and propose a new data cleansing method that improves clustering quality and performance. We evaluate our data cleansing method through a series of experiments. As a result, the clustering quality and performance were significantly improved by up to 165% and 330%, respectively.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copy
Woong-Kee LOH, Yang-Sae MOON, Jun-Gyu KANG, "A Data Cleansing Method for Clustering Large-Scale Transaction Databases" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 11, pp. 3120-3123, November 2010, doi: 10.1587/transinf.E93.D.3120.
Abstract: In this paper, we emphasize the need for data cleansing when clustering large-scale transaction databases and propose a new data cleansing method that improves clustering quality and performance. We evaluate our data cleansing method through a series of experiments. As a result, the clustering quality and performance were significantly improved by up to 165% and 330%, respectively.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.3120/_p
Copy
@ARTICLE{e93-d_11_3120,
author={Woong-Kee LOH, Yang-Sae MOON, Jun-Gyu KANG, },
journal={IEICE TRANSACTIONS on Information},
title={A Data Cleansing Method for Clustering Large-Scale Transaction Databases},
year={2010},
volume={E93-D},
number={11},
pages={3120-3123},
abstract={In this paper, we emphasize the need for data cleansing when clustering large-scale transaction databases and propose a new data cleansing method that improves clustering quality and performance. We evaluate our data cleansing method through a series of experiments. As a result, the clustering quality and performance were significantly improved by up to 165% and 330%, respectively.},
keywords={},
doi={10.1587/transinf.E93.D.3120},
ISSN={1745-1361},
month={November},}
Copy
TY - JOUR
TI - A Data Cleansing Method for Clustering Large-Scale Transaction Databases
T2 - IEICE TRANSACTIONS on Information
SP - 3120
EP - 3123
AU - Woong-Kee LOH
AU - Yang-Sae MOON
AU - Jun-Gyu KANG
PY - 2010
DO - 10.1587/transinf.E93.D.3120
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2010
AB - In this paper, we emphasize the need for data cleansing when clustering large-scale transaction databases and propose a new data cleansing method that improves clustering quality and performance. We evaluate our data cleansing method through a series of experiments. As a result, the clustering quality and performance were significantly improved by up to 165% and 330%, respectively.
ER -