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» An overview of clustering methods
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177
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PKDD
1999
Springer
130views Data Mining» more  PKDD 1999»
15 years 11 months ago
OPTICS-OF: Identifying Local Outliers
: For many KDD applications finding the outliers, i.e. the rare events, is more interesting and useful than finding the common cases, e.g. detecting criminal activities in E-commer...
Markus M. Breunig, Hans-Peter Kriegel, Raymond T. ...
190
Voted
CLEF
2008
Springer
15 years 8 months ago
Using Visual Concepts and Fast Visual Diversity to Improve Image Retrieval
In this article, we focus our efforts (i) on the study of how to automatically extract and exploit visual concepts and (ii) on fast visual diversity. First, in the Visual Concept D...
Sabrina Tollari, Marcin Detyniecki, Ali Fakeri-Tab...
173
Voted
CLEF
2010
Springer
15 years 8 months ago
Using Web Graph Structure for Person Name Disambiguation
In the third edition of WePS campaign we have undertaken the person name disambiguation problem referred to as a clustering task. Our aim was to make use of intrinsic link relation...
Elena Smirnova, Konstantin Avrachenkov, Brigitte T...
206
Voted
IEEEVAST
2010
15 years 1 months ago
Finding and visualizing relevant subspaces for clustering high-dimensional astronomical data using connected morphological opera
Data sets in astronomy are growing to enormous sizes. Modern astronomical surveys provide not only image data but also catalogues of millions of objects (stars, galaxies), each ob...
Bilkis J. Ferdosi, Hugo Buddelmeijer, Scott Trager...
204
Voted
CVPR
2007
IEEE
16 years 9 months ago
Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data
A popular approach to problems in image classification is to represent the image as a bag of visual words and then employ a classifier to categorize the image. Unfortunately, a si...
Liu Yang, Rong Jin, Caroline Pantofaru, Rahul Sukt...