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» OP-Cluster: Clustering by Tendency in High Dimensional Space
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ICDM
2007
IEEE
137views Data Mining» more  ICDM 2007»
14 years 1 months ago
Locally Constrained Support Vector Clustering
Support vector clustering transforms the data into a high dimensional feature space, where a decision function is computed. In the original space, the function outlines the bounda...
Dragomir Yankov, Eamonn J. Keogh, Kin Fai Kan
MICCAI
2005
Springer
14 years 8 months ago
White Matter Tract Clustering and Correspondence in Populations
We present a novel method for finding white matter fiber correspondences and clusters across a population of brains. Our input is a collection of paths from tractography in every b...
Lauren O'Donnell, Carl-Fredrik Westin
EMNLP
2009
13 years 5 months ago
Improving Verb Clustering with Automatically Acquired Selectional Preferences
In previous research in automatic verb classification, syntactic features have proved the most useful features, although manual classifications rely heavily on semantic features. ...
Lin Sun, Anna Korhonen
ACL
2006
13 years 9 months ago
Unsupervised Relation Disambiguation Using Spectral Clustering
This paper presents an unsupervised learning approach to disambiguate various relations between name entities by use of various lexical and syntactic features from the contexts. I...
Jinxiu Chen, Dong-Hong Ji, Chew Lim Tan, Zheng-Yu ...
EDBT
2008
ACM
132views Database» more  EDBT 2008»
14 years 7 months ago
Indexing high-dimensional data in dual distance spaces: a symmetrical encoding approach
Due to the well-known dimensionality curse problem, search in a high-dimensional space is considered as a "hard" problem. In this paper, a novel symmetrical encoding-bas...
Yi Zhuang, Yueting Zhuang, Qing Li, Lei Chen 0002,...