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EDBT
2008
ACM
167views Database» more  EDBT 2008»
16 years 6 months ago
HISSCLU: a hierarchical density-based method for semi-supervised clustering
In situations where class labels are known for a part of the objects, a cluster analysis respecting this information, i.e. semi-supervised clustering, can give insight into the cl...
Christian Böhm, Claudia Plant
JCB
2002
160views more  JCB 2002»
15 years 6 months ago
Inference from Clustering with Application to Gene-Expression Microarrays
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different u...
Edward R. Dougherty, Junior Barrera, Marcel Brun, ...
OODBS
2000
110views Database» more  OODBS 2000»
15 years 10 months ago
Opportunistic Prioritised Clustering Framework (OPCF)
Ever since the `early days' of database management systems, clustering has proven to be one of the most effective performance enhancement techniques for object oriented datab...
Zhen He, Alonso Marquez, Stephen Blackburn
EMNLP
2011
14 years 6 months ago
Unsupervised Dependency Parsing without Gold Part-of-Speech Tags
We show that categories induced by unsupervised word clustering can surpass the performance of gold part-of-speech tags in dependency grammar induction. Unlike classic clustering ...
Valentin I. Spitkovsky, Hiyan Alshawi, Angel X. Ch...
ISBI
2004
IEEE
16 years 7 months ago
Robust Unsupervised Tissue Classification in MR Images
A general framework for performing robust, unsupervised tissue classification in magnetic resonance images is presented. Tissue classification is formulated as an estimation probl...
Dzung L. Pham, Jerry L. Prince