@inproceedings{bfb88fea5da74c43b109db4280c59e72,
title = "Metric incremental clustering of nominal data",
abstract = "We present an algorithm for clustering nominal data that is based on a metric on the set of partitions of a finite set of objects; this metric is defined starting from a lower valuation of the lattice of partitions. The proposed algorithm seeks to determine a clustering partition such that the total distance between this partition and the partitions determined by the attributes of the objects has a local minimum. The resulting clustering is quite stable relative to the ordering of the objects.",
author = "Dan Simovici and Namita Singla and Michael Kuperberg",
year = "2004",
doi = "10.1109/ICDM.2004.10005",
language = "English",
isbn = "0769521428",
series = "Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004",
pages = "523--526",
editor = "R. Rastogi and K. Morik and M. Bramer and X. Wu",
booktitle = "Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004",
note = "Proceedings - Fourth IEEE International Conference on Data Mining, ICDM 2004 ; Conference date: 01-11-2004 Through 04-11-2004",
}