Formalizing complex prior information to quantify subjective interestingness of frequent pattern sets

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7619 LNCS, Issue , 2012, Pages 161-171

  Kontonasios, Kleanthis Nikolaos ^a   Debie, Tijl ^a  

^a UNIVERSITY OF BRISTOL   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTER STRUCTURE; DATA MINERS; INTERESTINGNESS; ITEM SETS; MARGINALS; MAXIMUM ENTROPY PRINCIPLE; PATTERN SET; PRIOR INFORMATION; REAL LIFE DATA;

ARTIFICIAL INTELLIGENCE;

INFORMATION THEORY;

EID: 84868026866     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-34156-4_16     Document Type: Conference Paper

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