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» Approximation algorithms for clustering uncertain data
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ICDM
2009
IEEE
121views Data Mining» more  ICDM 2009»
14 years 2 months ago
Finding Time Series Motifs in Disk-Resident Data
—Time series motifs are sets of very similar subsequences of a long time series. They are of interest in their own right, and are also used as inputs in several higher-level data...
Abdullah Mueen, Eamonn J. Keogh, Nima Bigdely Sham...
IIS
2003
13 years 9 months ago
Web Search Results Clustering in Polish: Experimental Evaluation of Carrot
Abstract. In this paper we consider the problem of web search results clustering in the Polish language, supporting our analysis with results acquired from an experimental system n...
Dawid Weiss, Jerzy Stefanowski
ECML
2006
Springer
13 years 11 months ago
Deconvolutive Clustering of Markov States
In this paper we formulate the problem of grouping the states of a discrete Markov chain of arbitrary order simultaneously with deconvolving its transition probabilities. As the na...
Ata Kabán, Xin Wang
SIGIR
2004
ACM
14 years 1 months ago
GaP: a factor model for discrete data
We present a probabilistic model for a document corpus that combines many of the desirable features of previous models. The model is called “GaP” for Gamma-Poisson, the distri...
John F. Canny
EMMCVPR
1997
Springer
13 years 11 months ago
Deterministic Annealing for Unsupervised Texture Segmentation
Abstract. In this paper a rigorous mathematical framework of deterministic annealing and mean-field approximation is presented for a general class of partitioning, clustering and ...
Thomas Hofmann, Jan Puzicha, Joachim M. Buhmann