DECODE: A new method for discovering clusters of different densities in spatial data

Data Mining and Knowledge Discovery

Volumn 18, Issue 3, 2009, Pages 337-369

  Pei, Tao ^a,b   Jasra, Ajay ^b   Hand, David J ^b   Zhu, A Xing ^a,c   Zhou, Chenghu ^a  

^a INSTITUTE OF GEOGRAPHIC SCIENCES AND NATURAL RESOURCES RESEARCH   (China)

^b IMPERIAL COLLEGE LONDON   (United Kingdom)

^c UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

Data mining; Earthquake; MCMC; Nearest neighbor; Point process; Reversible jump

Indexed keywords

CLASSIFICATION ,; CLUSTER METHODS; DENSITY-BASED; MCMC; MODEL-BASED APPROACHES; NEAREST NEIGHBOR; POINT PROCESS; PRIOR KNOWLEDGE; REVERSIBLE JUMP; REVERSIBLE JUMP MARKOV CHAIN MONTE CARLO; REVERSIBLE JUMP MCMC; SEISMIC DATUM; SIMULATED DATA SETS; SIMULATED DATUM; SPATIAL DATUM; SPATIAL POINTS; STATE-OF-THE-ART METHODS; STRESS DISTRIBUTIONS; TWO POINTS;

BINS; INFORMATION MANAGEMENT; MARKOV PROCESSES; SEISMIC RESPONSE; SEISMIC WAVES; STRESS CONCENTRATION;

EARTHQUAKES;

EID: 65049086084     PISSN: 13845810     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10618-008-0120-3     Document Type: Article

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