@inproceedings{d37e038549944a6ebabb861ac2897ed1,
title = "Cluster validity through graph-based boundary analysis",
abstract = "Gaining confidence that a clustering algorithm has produced meaningful results and not an accident of its usually heuristic optimization is central to data mining. This is the issue of cluster validity. We propose here a method by which proximity graphs are used to effectively detect border points and measure the margin between clusters. With analysis of boundary situation, we design a framework and relevant working principles to evaluate the separation and compactness in the clustering results. The method can obtain an insight into the internal structure in clustering result.",
keywords = "Cluster Validity, Clustering, Data Mining, Proximity Graph",
author = "Jianhua Yang and Ickjai Lee",
year = "2004",
language = "English",
isbn = "1932415270",
series = "Proceedings of the International Conference on Information and Knowledge Engineering , IKE'04",
pages = "204--210",
editor = "H.R. Arabnia",
booktitle = "Proceedings of the International Conference on Information and Knowledge Engineering, IKE'04",
note = "Proceedings of the International Conference on Information and Knowledge Engineering, IKE'04 ; Conference date: 21-06-2004 Through 24-06-2004",
}