Domain-driven KDD for mining functionally novel rules and linking disjoint medical hypotheses

Knowledge-Based Systems

Volumn 24, Issue 5, 2011, Pages 609-620

  Sebastian, Y ^a   Then, Patrick H H ^a  

^a SWINBURNE UNIVERSITY OF TECHNOLOGY   (Malaysia)

Author keywords

Association rules; Data mining methods; Interactive data exploration and discovery; Medical knowledge support systems; Rule interestingness

Indexed keywords

DATA MINING METHODS; DATA MINING SYSTEM; DATA SETS; DIABETES MELLITUS; DOMAIN KNOWLEDGE; INTERACTIVE DATA EXPLORATION; INTERESTING RULES; MEDICAL KNOWLEDGE; NOVEL DOMAIN; POST PROCESSING; RULE EVALUATION; RULE INTERESTINGNESS; VON WILLEBRAND FACTOR;

ASSOCIATION RULES; DATA MINING; MEDICAL EDUCATION; ONTOLOGY; SEMANTICS;

MEDICAL COMPUTING;

EID: 79955072070     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2011.01.008     Document Type: Article

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