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KDD
2004
ACM
150views Data Mining» more  KDD 2004»
16 years 6 months ago
A framework for ontology-driven subspace clustering
Traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. While domain knowledge is always the bes...
Jinze Liu, Wei Wang 0010, Jiong Yang
BMCBI
2010
214views more  BMCBI 2010»
15 years 6 months ago
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Aaron M. Newman, James B. Cooper
ICPR
2008
IEEE
16 years 7 months ago
Geodesic K-means clustering
We introduce a class of geodesic distances and extend the K-means clustering algorithm to employ this distance metric. Empirically, we demonstrate that our geodesic K-means algori...
Arian Maleki, Nima Asgharbeygi
EUC
2005
Springer
15 years 12 months ago
Neighbor Node Discovery Algorithm for Energy-Efficient Clustering in Ubiquitious Sensor Networks
Clustering algorithm is an essential element to implement a hierarchical routing protocol, especially for a large-scale wireless sensor network. In this paper, we propose a new typ...
Ji Young Choi, Chung Gu Kang, Yong-Suk Kim, Kyeong...
AI
2006
Springer
15 years 10 months ago
A New Profile Alignment Method for Clustering Gene Expression Data
We focus on clustering gene expression temporal profiles, and propose a novel, simple algorithm that is powerful enough to find an efficient distribution of genes over clusters. We...
Ataul Bari, Luis Rueda