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ICCV
2009
IEEE
15 years 1 months ago
Mode-Detection via Median-Shift
Median-shift is a mode seeking algorithm that relies on computing the median of local neighborhoods, instead of the mean. We further combine median-shift with Locality Sensitive...
Lior Shapira, Shai Avidan, Ariel Shamir
ICDM
2005
IEEE
189views Data Mining» more  ICDM 2005»
14 years 2 months ago
Integrating Hidden Markov Models and Spectral Analysis for Sensory Time Series Clustering
We present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. The sensory time-series data present new challenges to da...
Jie Yin, Qiang Yang
LWA
2007
13 years 10 months ago
Multi-objective Frequent Termset Clustering
Large, high dimensional data spaces, are still a challenge for current data clustering methods. Frequent Termset (FTS) clustering is a technique developed to cope with these chall...
Andreas Kaspari, Michael Wurst
SDM
2009
SIAM
167views Data Mining» more  SDM 2009»
14 years 5 months ago
Parallel Pairwise Clustering.
Given the pairwise affinity relations associated with a set of data items, the goal of a clustering algorithm is to automatically partition the data into a small number of homogen...
Elad Yom-Tov, Noam Slonim
KDD
2006
ACM
145views Data Mining» more  KDD 2006»
14 years 9 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...