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SIGMOD
1998
ACM
233views Database» more  SIGMOD 1998»
15 years 9 months ago
Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications
Data mining applications place special requirements on clustering algorithms including: the ability to nd clusters embedded in subspaces of high dimensional data, scalability, end...
Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopul...
159
Voted
SDM
2007
SIAM
117views Data Mining» more  SDM 2007»
15 years 6 months ago
Discriminating Subsequence Discovery for Sequence Clustering
In this paper, we explore the discriminating subsequencebased clustering problem. First, several effective optimization techniques are proposed to accelerate the sequence mining p...
Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Ka...
ECIR
2006
Springer
15 years 6 months ago
Phrase Clustering Without Document Context
Abstract. We applied different clustering algorithms to the task of clustering multi-word terms in order to reflect a humanly built ontology. Clustering was done without the usual ...
Eric SanJuan, Fidelia Ibekwe-Sanjuan
SODA
2010
ACM
189views Algorithms» more  SODA 2010»
16 years 2 months ago
Correlation Clustering with Noisy Input
Correlation clustering is a type of clustering that uses a basic form of input data: For every pair of data items, the input specifies whether they are similar (belonging to the s...
Claire Mathieu, Warren Schudy
SIGMOD
2008
ACM
107views Database» more  SIGMOD 2008»
16 years 5 months ago
Outlier-robust clustering using independent components
How can we efficiently find a clustering, i.e. a concise description of the cluster structure, of a given data set which contains an unknown number of clusters of different shape ...
Christian Böhm, Christos Faloutsos, Claudia P...