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IDA
2005
Springer
15 years 12 months ago
From Local Pattern Mining to Relevant Bi-cluster Characterization
Clustering or bi-clustering techniques have been proved quite useful in many application domains. A weakness of these techniques remains the poor support for grouping characterizat...
Ruggero G. Pensa, Jean-François Boulicaut
GIS
2008
ACM
16 years 7 months ago
Privacy: preserving trajectory collection
In order to provide context?aware Location?Based Services, real location data of mobile users must be collected and analyzed by spatio?temporal data mining methods. However, the d...
Gyözö Gidófalvi, Torben Bach Pede...
ICDM
2005
IEEE
189views Data Mining» more  ICDM 2005»
16 years 4 hour 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
AICCSA
2008
IEEE
292views Hardware» more  AICCSA 2008»
16 years 26 days ago
Enumeration of maximal clique for mining spatial co-location patterns
This paper presents a systematic approach to mine colocation patterns in Sloan Digital Sky Survey (SDSS) data. SDSS Data Release 5 (DR5) contains 3.6 TB of data. Availability of s...
Ghazi Al-Naymat
BMCBI
2008
121views more  BMCBI 2008»
15 years 6 months ago
Microarray data mining using landmark gene-guided clustering
Background: Clustering is a popular data exploration technique widely used in microarray data analysis. Most conventional clustering algorithms, however, generate only one set of ...
Pankaj Chopra, Jaewoo Kang, Jiong Yang, HyungJun C...