@inproceedings{3c3985e03629463a9dfc3d3e36e7865b,
title = "Coe: Clustering with obstacles entities a preliminary study",
abstract = "Clustering analysis has been a very active area of research in the data mining community. However, most algorithms have ignored the tact that physical obstacles exist in the real world and could thus aiffect the result of clustering dramatically. In this paper, we will look at the problem of clustering in the presence of obstacles. We called this problem the COE (Clustering with Obstaicles Entities) problem and provide an outhne of an algorithm called COE-CLARANS to solve it.",
author = "Tung, {Anthony K.H.} and Jean Hon and Jiawei Han",
year = "2000",
doi = "10.1007/3-540-45571-x_19",
language = "English (US)",
isbn = "3540673822",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "165--168",
editor = "Takao Terano and Huan Liu and Chen, {Arbee L.P.}",
booktitle = "Knowledge Discovery and Data Mining",
address = "Germany",
note = "4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2000 ; Conference date: 18-04-2000 Through 20-04-2000",
}