Jan Rauch

Jan Rauch: Observational Calculi and Association Rules. Studies in Computational Intelligence 469, Springer 2013, isbn 978-3-642-11736-7, pp. 1-282

Jan Rauch: EverMiner: consideration on knowledge driven permanent data mining process. IJDMMM 4(3): 224-243 (2012)

Jan Rauch: Domain Knowledge and Data Mining with Association Rules - A Logical Point of View. ISMIS 2012: 11-20

Tapio Elomaa, Petr Berka, Jan Rauch: Special issue on data analysis methodologies for intelligent systems: guest editor's introduction. J. Intell. Inf. Syst. 37(3): 291-292 (2011)

Jan Rauch: Consideration on a formal frame for data mining. GrC 2011: 562-569

Jan Rauch, Milan Simunek: Applying Domain Knowledge in Association Rules Mining Process - First Experience. ISMIS 2011: 113-122

Jan Rauch, Milan Simunek: Dealing with domain knowledge in association rules mining - Several experiments. ICDKE 2011: 13-17

Petr Hájek, Martin Holena, Jan Rauch: The GUHA method and its meaning for data mining. J. Comput. Syst. Sci. 76(1): 34-48 (2010)

Jan Rauch: Modifying Logic of Discovery for Dealing with Domain Knowledge in Data Mining. CLA 2010: 175-186

Petr Berka, Jan Rauch: Meta-learning for Post-processing of Association Rules. DaWak 2010: 251-262

Jan Rauch: Logic of Discovery, Data Mining and Semantic Web - Position Paper. KDIR 2010: 342-351

Petr Berka, Jan Rauch: Mining and Post-processing of Association Rules in the Atherosclerosis Risk Domain. ITBAM 2010: 110-117

Tomás Kliegr, Jan Rauch: An XML Format for Association Rule Models Based on the GUHA Method. RuleML 2010: 273-288

Jan Rauch: Logical Aspects of the Measures of Interestingness of Association Rules. Advances in Machine Learning II 2010: 175-203

Jan Rauch, Milan Simunek: Action Rules and the GUHA Method: Preliminary Considerations and Results. ISMIS 2009: 76-87

Jan Rauch, Zbigniew W. Ras, Petr Berka, Tapio Elomaa (Eds.): Foundations of Intelligent Systems, 18th International Symposium, ISMIS 2009, Prague, Czech Republic, September 14-17, 2009. Proceedings. Lecture Notes in Computer Science 5722, Springer 2009, isbn 978-3-642-04124-2

Jan Rauch: Remarks to Logical Aspects of Measures of Interestingness of Association Rules. ICDM Workshops 2008: 599-608

Jan Rauch, Milan Simunek: LAREDAM - Considerations on System of Local Analytical Reports from Data Mining. ISMIS 2008: 143-149

Jan Rauch: Classes of Association Rules: An Overview. Data Mining: Foundations and Practice 2008: 315-337

Petr Berka, Jan Rauch, Marie Tomecková: Lessons Learned from the ECML/PKDD Discovery Challenge on the Atherosclerosis Risk Factors Data. Computing and Informatics 26(3): 329-344 (2007)

Jan Rauch: Observational Calculi, Classes of Association Rules and F-property. GrC 2007: 287-293

Jan Rauch: Project SEWEBAR Considerations on Semantic Web and Data Mining. IICAI 2007: 1763-1782

Jan Rauch, Milan Simunek: Semantic Web Presentation of Analytical Reports from Data Mining - Preliminary Considerations. Web Intelligence 2007: 3-7

Patrik Eklund, Johan Karlsson, Jan Rauch, Milan Simunek: On the Logic of Medical Decision Support. Theory and Applications of Relational Structures as Knowledge Instruments 2006: 50-59

Jan Rauch: Many Sorted Observational Calculi for Multi-Relational Data Mining. ICDM Workshops 2006: 417-422

Jan Rauch: Definability of Association Rules in Predicate Calculus. Foundations and Novel Approaches in Data Mining 2006: 23-40

Jan Rauch, Milan Simunek, Václav Lín: Mining for Patterns Based on Contingency Tables by KL-Miner - First Experience. Foundations and Novel Approaches in Data Mining 2006: 155-167

Jan Rauch: Logic of Association Rules. Appl. Intell. 22(1): 9-28 (2005)

Vojtech Svátek, Jan Rauch, Martin Ralbovský: Ontology-Enhanced Association Mining. EWMF/KDO 2005: 163-179

Jan Rauch, Milan Simunek: GUHA method and granular computing. GrC 2005: 630-635

Jan Rauch, Milan Simunek: An Alternative Approach to Mining Association Rules. Foundations of Data Mining and knowledge Discovery 2005: 211-231

Petr Strossa, Zdenek Cerný, Jan Rauch: Reporting Data Mining Results in a Natural Language. Foundations of Data Mining and knowledge Discovery 2005: 347-361

Petr Hájek, Jan Rauch, David Coufal, Thomas Feglar: The GUHA Method, Data Preprocessing and Mining. Database Support for Data Mining Applications 2004: 135-153

Tomás Karban, Jan Rauch, Milan Simunek: SDS-rules and association rules. SAC 2004: 520-524

Petr Hájek, Martin Holena, Jan Rauch: The GUHA Method and Foundations of (Relational) Data Mining. Theory and Applications of Relational Structures as Knowledge Instruments 2003: 17-37

Petr Strossa, Jan Rauch: Converting Association Rules into Natural Language - an Attempt. IIS 2003: 383-392

Václav Lín, Jan Rauch, Vojtech Svátek: Mining and Querying in Association Rule Discovery. KDID 2002: 97-98

Václav Lín, Jan Rauch, Vojtech Svátek: Content-based Retrieval of Analytical Reports. RuleML 2002

Jan Rauch, Milan Simunek: Mining for Association Rules by 4ft-Miner. INAP 2001: 285-295

Jan Rauch, Milan Simunek: Mining for 4ft Association Rules. Discovery Science 2000: 268-272

Jan Rauch: Deduction in Logic of Association Rules. ASIAN 1999: 386-387

Petr Hájek, Jan Rauch: Logics and Statistics for Association Rules and Beyond Abstract of Tutorial. PKDD 1999: 586-587

Jan M. Zytkow, Jan Rauch (Eds.): Principles of Data Mining and Knowledge Discovery, Third European Conference, PKDD '99, Prague, Czech Republic, September 15-18, 1999, Proceedings. Lecture Notes in Computer Science 1704, Springer 1999, isbn 3-540-66490-4

Jan Rauch: Four-Fold Table Calculi for Discovery Science. Discovery Science 1998: 405-406

Jan Rauch: Classes of Four-Fold Table Quantifiers. PKDD 1998: 203-211

Jan Rauch: Logical Calculi for Knowledge Discovery in Databases. PKDD 1997: 47-57

Jan Rauch: Main Problems and Further Possibilities of the Computer Realization of GUHA Procedures. International Journal of Man-Machine Studies 15(3): 283-287 (1981)