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» Data Clustering: A Review
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LREC
2010
114views Education» more  LREC 2010»
15 years 8 months ago
The VeteranTapes: Research Corpus, Fragment Processing Tool, and Enhanced Publications for the e-Humanities
Enhanced Publications are a new way to publish scientific and other results in an electronic article. The advantage of EPs is that the relation between the article and the underly...
Henk van den Heuvel, René van Horik, Stef S...
ICDM
2007
IEEE
132views Data Mining» more  ICDM 2007»
16 years 28 days ago
Error-Aware Density-Based Clustering of Imprecise Measurement Values
Manufacturing process development is under constant pressure to achieve a good yield for stable processes. The development of new technologies, especially in the field of photoma...
Dirk Habich, Peter Benjamin Volk, Wolfgang Lehner,...
KDD
2004
ACM
624views Data Mining» more  KDD 2004»
15 years 12 months ago
Programming the K-means clustering algorithm in SQL
Using SQL has not been considered an efficient and feasible way to implement data mining algorithms. Although this is true for many data mining, machine learning and statistical a...
Carlos Ordonez
ITSL
2008
15 years 8 months ago
An Empirical Comparison of NML Clustering Algorithms
Clustering can be defined as a data assignment problem where the goal is to partition the data into nonhierarchical groups of items. In our previous work, we suggested an informati...
Petri Kontkanen, Petri Myllymäki
ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
16 years 11 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer