Coe: Clustering with obstacles entities a preliminary study

Anthony K.H. Tung, Jean Hon, Jiawei Han

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationKnowledge Discovery and Data Mining
Subtitle of host publicationCurrent Issues and New Applications - 4th Pacific-Asia Conference, PAKDD 2000, Proceedings
EditorsTakao Terano, Huan Liu, Arbee L.P. Chen
PublisherSpringer
Pages165-168
Number of pages4
ISBN (Print)3540673822, 9783540673828
DOIs
StatePublished - Jan 1 2000
Externally publishedYes
Event4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2000 - Kyoto, Japan
Duration: Apr 18 2000Apr 20 2000

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1805
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2000
Country/TerritoryJapan
CityKyoto
Period4/18/004/20/00

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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