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KDD
2004
ACM
624views Data Mining» more  KDD 2004»
16 years 3 hour 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
ICMCS
2006
IEEE
94views Multimedia» more  ICMCS 2006»
16 years 20 days ago
Semantic Labeling of Multimedia Content Clusters
In this paper we present a novel approach for labeling clusters of multimedia content that leverages supervised classification techniques in conjunction with unsupervised cluster...
Jelena Tesic, John R. Smith
SSPR
2004
Springer
15 years 12 months ago
Clustering Variable Length Sequences by Eigenvector Decomposition Using HMM
We present a novel clustering method using HMM parameter space and eigenvector decomposition. Unlike the existing methods, our algorithm can cluster both constant and variable leng...
Fatih Murat Porikli