@inproceedings{c810c519a1fb4f2b9ce3101974d40261,
title = "A data partitioning approach for hierarchical clustering",
abstract = "In this paper, we propose a parameter-insensitive data partitioning approach for Chameleon, a hierarchical clustering algorithm. The proposed method splits a given dataset into every possible number of clusters by using existing algorithms that do allow arbitrary-sized sub-clusters in partitioning. After that, it evaluates the quality of every set of initial sub-clusters by using our measurement function, and decides the optimal set of initial sub-clusters such that they show the highest value of measurement. Finally, it merges these optimal initial sub-clusters repeatedly and produces the final clustering result. We perform extensive experiments, and the results show that the proposed approach is insensitive to parameters and also produces a set of final clusters whose quality is better than the previous one.",
keywords = "Data partitioning, Hierarchical clustering, Parameter-insensitive",
author = "Yoon, \{Seok Ho\} and Song, \{Suk Soon\} and Lee, \{Sang Chul\} and Jeong, \{Kyo Sung\} and Kim, \{Sang Wook\} and Sooyong Kang and Choi, \{Yong Suk\} and Jaehyuk Cha and Minsoo Ryu and Jeong, \{Byung Soo\}",
year = "2013",
doi = "10.1145/2448556.2448628",
language = "English",
isbn = "9781450319584",
series = "Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2013",
booktitle = "Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2013",
note = "7th International Conference on Ubiquitous Information Management and Communication, ICUIMC 2013 ; Conference date: 17-01-2013 Through 19-01-2013",
}