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ECML
2001
Springer
15 years 11 months ago
Iterative Double Clustering for Unsupervised and Semi-supervised Learning
We present a powerful meta-clustering technique called Iterative Double Clustering (IDC). The IDC method is a natural extension of the recent Double Clustering (DC) method of Slon...
Ran El-Yaniv, Oren Souroujon
SDM
2007
SIAM
107views Data Mining» more  SDM 2007»
15 years 8 months ago
On Demand Phenotype Ranking through Subspace Clustering
High throughput biotechnologies have enabled scientists to collect a large number of genetic and phenotypic attributes for a large collection of samples. Computational methods are...
Xiang Zhang, Wei Wang 0010, Jun Huan
ACL
2001
15 years 8 months ago
Multi-Class Composite N-gram Language Model for Spoken Language Processing Using Multiple Word Clusters
In this paper, a new language model, the Multi-Class Composite N-gram, is proposed to avoid a data sparseness problem for spoken language in that it is difficult to collect traini...
Hirofumi Yamamoto, Shuntaro Isogai, Yoshinori Sagi...
IS
2006
15 years 6 months ago
A methodology for clustering XML documents by structure
The processing and management of XML data are popular research issues. However, operations based on the structure of XML data have not received strong attention. These operations ...
Theodore Dalamagas, Tao Cheng, Klaas-Jan Winkel, T...
PVLDB
2010
86views more  PVLDB 2010»
15 years 5 months ago
Swarm: Mining Relaxed Temporal Moving Object Clusters
Recent improvements in positioning technology make massive moving object data widely available. One important analysis is to find the moving objects that travel together. Existin...
Zhenhui Li, Bolin Ding, Jiawei Han, Roland Kays