Exploiting background knowledge for knowledge-intensive subgroup discovery

IJCAI International Joint Conference on Artificial Intelligence

Volumn , Issue , 2005, Pages 647-652

  Atzmueller, Martin ^a   Puppe, Frank ^a   Buscher, Hans Peter ^b  

^a UNIVERSITY OF WÜRZBURG   (Germany)

^b German Red Cross Hospital   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

BACK-GROUND KNOWLEDGE; DATA MINING METHODS; INTERESTINGNESS; ITS APPLICATIONS; MEDICAL DOCUMENTATION; MEDICAL DOMAINS; PROCESS MODEL; SUBGROUP DISCOVERY;

ARTIFICIAL INTELLIGENCE;

EID: 79960812445     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

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2. Joachim Baumeister, Martin Atzmueller, and Frank Puppe. Inductive Learning for Case-Based Diagnosis with Multiple Faults. In Advances in Case-Based Reasoning, volume 2416 of LNAI, pages 28-42, Berlin, 2002. Springer Verlag.
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10. Irene Weber. Levelwise search and Pruning Strategies for First-Order Hypothesis Spaces. Journal of Intelligent Information Systems, 14:217-239, 2000.
11. Stefan Wrobel. An Algorithm for Multi-Relational Discovery of Subgroups. In Proc. 1st European Symposion on Principles of Data Mining and Knowledge Discovery, pages 78-87, Berlin, 1997. Springer Verlag.
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