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» The Practice of Cluster Analysis
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138
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SIGIR
2002
ACM
15 years 3 months ago
Analysis of papers from twenty-five years of SIGIR conferences: what have we been doing for the last quarter of a century?
mes, abstracts and year of publication of all 853 papers published.1 We then applied Porter stemming and stopword removal to this text, represented terms from the elds with twice t...
Alan F. Smeaton, Gary Keogh, Cathal Gurrin, Kieran...
115
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ICML
2006
IEEE
16 years 4 months ago
Combined central and subspace clustering for computer vision applications
Central and subspace clustering methods are at the core of many segmentation problems in computer vision. However, both methods fail to give the correct segmentation in many pract...
Le Lu, René Vidal
129
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ITNG
2010
IEEE
15 years 8 months ago
A Fast and Stable Incremental Clustering Algorithm
— Clustering is a pivotal building block in many data mining applications and in machine learning in general. Most clustering algorithms in the literature pertain to off-line (or...
Steven Young, Itamar Arel, Thomas P. Karnowski, De...
KDD
1998
ACM
123views Data Mining» more  KDD 1998»
15 years 7 months ago
Scaling Clustering Algorithms to Large Databases
Practical clustering algorithms require multiple data scans to achieve convergence. For large databases, these scans become prohibitively expensive. We present a scalable clusteri...
Paul S. Bradley, Usama M. Fayyad, Cory Reina
135
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COLT
2008
Springer
15 years 5 months ago
Model Selection and Stability in k-means Clustering
Clustering Stability methods are a family of widely used model selection techniques applied in data clustering. Their unifying theme is that an appropriate model should result in ...
Ohad Shamir, Naftali Tishby