Rule mining and classification in a situation assessment application: A belief-theoretic approach for handling data imperfections

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 37, Issue 6, 2007, Pages 1446-1459

  Rohitha, K K ^a   Hewawasam, G K ^a   Premaratne, Kamal ^a   Shyu, Mei Ling ^a  

^a University of Miami College of Engineering   (United States)

Author keywords

Association rule mining (ARM); Classification; Data imperfections; Data mining; Dempster Shafer (DS) belief theory; Situation assessment; Uncertainty handling

Indexed keywords

ALGORITHMS; ASSOCIATION RULES; CLASSIFICATION (OF INFORMATION); DATA MINING; DATABASE SYSTEMS; DECISION MAKING;

ASSOCIATION RULE MINING; DATA IMPERFECTION; DEMPSTER-SHAFER BELIEF THEORY; SITUATION ASSESSMENT;

DATA PROCESSING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER SIMULATION; DATA BASE; FACTUAL DATABASE; INFORMATION RETRIEVAL; METHODOLOGY; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DATABASE MANAGEMENT SYSTEMS; DATABASES, FACTUAL; INFORMATION STORAGE AND RETRIEVAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED;

EID: 36749083967     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2007.903536     Document Type: Article

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