References

 

References

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[BI 94]
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[BR 98]
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[BR 03]
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[Bu 03]
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[Bu 04]
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[CDRS 03]
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[Ce 03]
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[COL 03]
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[DLRS 02]
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[GH+]
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[Ha 66A]
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[Ha 66B]
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[Ha 78]
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[HR 99]
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[HSZ 95]
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[Hv 81]
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[HMS 01]
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[IS 88]
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[Iv 99]
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[Ka 04]
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[Ke 04]
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[KRS 04]
Karban, T. – Rauch, J. – Šimůnek, M.: SDS-Rules and Association Rules.
[LRS 02A]
Lín, V. – Rauch, J. – Svátek, V.: Contend-based Retrieval of Analytic Reports. In: SCHROEDER, Michael, WAGNER, Gerd (ed.). Rule Markup Languages for Business Rules on the Semantic Web. Sardinia: ISWC, 2002, pp. 219–224.
[LRS 02B]
Lín, V. – Rauch, J. – Svátek, V.: Analytic Reports from KDD: Integration into Semantic Web. In: ISWC 2002. Cagliari: University of Cagliari, 2002, p. 38.
[LRS 02C]
Lín, V. – Rauch, J. – Svátek, V.: Mining and Querying in Association Rule Discovery. In: KLEMETTINEN, Mika, MEO, Rosa, GIANNOTTI, Fosca, DE RAEDT, Luc (ed.). Knowledge Discovery in Inductive Databases – KDID '02. Helsinki: University of Helsinki, 2002, pp. 97–98. ISBN 952-10-0638-2.
[Ra 71]
Rauch, J.: Application of three-valued logic for GUHA method. Diploma work. Faculty of mathematics and Physics Charles University Prague, 1971 42 pp, (in Czech).
[Ra 78]
Rauch, J.: Some Remarks on Computer Realisations of GUHA Procedures. International Journal of Man-Machine Studies, 10, (1978), pp. 23–28.
[Ra 81]
Rauch, J.: Main Problems and Further Possibilities of the Computer Realizations of GUHA Procedures. International Journal of Man-Machine Studies, 15, 1981, pp. 283–287.
[Ra 86]
Rauch, J.: Logical Foundations of Hypothesis Formation from Databases, Mathematical Institute of the Czechoslovak Academy of Sciences, Prague, Czech Republic, PhD. thesis, 1986 (in Czech).
[PR 81]
Pokorný, J. – Rauch, J.: The GUHA-DBS database system. International Journal of Man-Machine Studies, 15, 1981, pp. 289–298.
[Ra 96]
Rauch, J.: GUHA as a Data Mining Tool. In: Practical Aspects of Knowledge Management. Schweizer Informatiker Gesellshaft Basel, 1996.
[Ra 97]
Rauch, J.: Logical Calculi for Knowledge Discovery in Databases. In Principles of Data Mining and Knowledge Discovery. Red. Komorowski, J. – Zytkow, J. Berlin, Springer Verlag 1997, pp. 47–57.
[Ra 98A]
Rauch, J.: Classes of Four Fold Table Quantifiers. In Principles of Data Mining and Knowledge Discovery. Red. Zytkow, J – Quafafou, M. Berlin, Springer Verlag 1998, pp. 203–211.
[Ra 98B]
Rauch, J.: Four-fold Table Calculi and Missing Information. In JCIS'98 Proceedings, (Paul P. Wang, editor), Association for Intelligent Machinery, pp. 375-378, 1998.
[Ra 98C]
Rauch, J.: Contribution to Logical Foundations of KDD: Inaugural Dissertation, University of Economics, Prague, 1998. 142 pp., (in Czech).
[Ra 98D]
Rauch, J.: Four-Fold Table Calculi for Discovery Science. In: ARIKAWA, Setsuo, MOTODA, Hiroshi (ed.). Discovery Science. Berlin : Springer, 1998, pp. 405–406. ISBN 3-540-65390-2.
[Ra 99]
Rauch, J.: Deduction in Logic of Association Rules. Lecture Notes in Computer Science 1742. ISBN 3-540-66856-X.
[RS 00]
Rauch, J. – Simunek, M.: Mining for 4ft Association Rules. In Discovery Science 2000. Red. Arikawa, S. – Morishita S. Springer Verlag 2000, pp. 268–272.
[Ra 01A]
Rauch, J.: Mining for Statistical Association Rules. In The Fifth Pacific-Asia Conference on Knowledge Discovery and Data Mining Industrial Track and Workshop Proceeding Red. Joseph Fong ang Michael Ng Hong Kong 2001, pp. 149–158.
[Ra 01B]
Rauch, J.: Association Rules and Mechanizing Hypothesis Formation. Working notes of ECML'2001 Workshop: Machine Learning as Experimental Philosophy of Science.
See also http://www.informatik.uni-freiburg.de/~ml/ecmlpkdd/.
[Ra 01C]
Rauch, J.: Mining for Association Rules in Financial Data. In: Seminar on Data Mining for Decision Support in Marketing. Porto : LIACC, 2001.
[Ra 01D]
Rauch, J.: System LISp-Miner – Example of Application. Acta Oeconomica Pragensia, 2001, Vol. 9, No 1, pp. 125–153. ISSN 0572-3043. (In Czech)
[Ra 02A]
Rauch, J.: Mining for Scientific Hypotheses. In Meij, J.(Editor): Dealing with the data flood. Mining Data, Text and Multimedia. STT/Beweton, The Hague. 2002. pp. 73–84.
[Ra 02B]
Rauch, J.: Interesting Association Rules and Multi-relational Association Rules. Communications of Institute of Information and Computing Machinery, Taiwan. Vol. 5, No. 2, May 2002, pp. 77–82.
[Ra 03]
Rauch, J.: Definability of Association Rules in Predicate Calculus. In: LIN, Tsau Young, HU, Xiaohua, OHSUGA, Setsuo, LIAU, C. J. (ed.). Data mining – Foundations and New Directions in Data Mining. Melbourne: IEEE Computer Society, 2003, pp. 148–155.
[RS 01A]
Rauch, J. – Šimůnek, M.: Mining for 4ft Rules. In: ARIKAWA, Setsuo, MORISHITA, Shinichi (ed.). Discovery Science. Berlin: Springer, 2000, pp. 268–272. ISBN 3-540-41352-9.
[RS 01B]
Rauch, J. – Simunek, M.: Mining for 4ft Association Rules by 4ft-Miner. in: INAP 2001, The Proceeding of the International Conference On Applications of Prolog. Prolog Association of Japan, Tokyo October 2001, pp. 285–294.
[RS 02]
Rauch, J. – Šimůnek, M.: Alternative Approach to Mining Association Rules. In: LIN, Tsau Young, OHSUGA, Setsuo (ed.). The Foundation of Data Mining and Knowledge Discovery (FDM02). Maebashi: Izumo, 2002, pp. 157–162. ISBN 4-947717-02-6.
[RS 03]
Rauch, J. – Šimůnek, M.: System LISp-Miner. In: SVÁTEK, Vojtěch (ed.). Znalosti 2003. Ostrava: TU Ostrava, 2003, pp. 83–92. ISBN 80-248-0229-5. (In Czech)
[RS 04]
Rauch, J – Šimůnek, M.: Project LISp-miner – current state and further development. In: SNÁŠEL, Václav (ed.). Znalosti 2004 – poster proceedings. Ostrava: VŠB TU, 2004, pp. 81–84. (In Czech)
[RSDL 04]
Rauch, J. – Šimůnek, M. – Dolejší, P. – Lín, V.: Data mining procedure KL-Miner. In: SNÁŠEL, Václav (ed.). Znalosti 2004. Ostrava: VŠB TU, 2004, pp. 350–361. ISBN 80-248-0456-5. (In Czech)
[RSL 03]
Rauch, J. – Šimůnek, M. – Lín, V.: Mining for Patterns Based on Contingency Tables by KL-Miner – First Experience. In: LIN, Tsau Young, HU, Xiaohua, OHSUGA, Setsuo, LIAU, C. J. (ed.). Data mining – Foundations and New Directions in Data Mining. Melbourne: IEEE Computer Society, 2003, pp. 156–163.
[RSC 03]
Rauch, J. – Strossa, P. – Černý, Z.: Reporting Data Mining Result in Natural Language. In: LIN, Tsau Young (ed.). Foundations and New Directions in Data Mining: Workshop Notes. Melbourne: IEEE Computer Society, 2003, pp. 164–171.
[Si 03]
Šimůnek, M.: Academic KDD Project LISp-Miner. In: ABRAHAM, A., FRANKE, K., KOPPEN, K. (ed.). Advances in Soft Computing – Intelligent Systems Desing and Applications. Heidelberg: Springer-Verlag, 2003, pp. 263–272. ISBN 3-540-40426-0.
[SSR 04]
Svátek, V. – Štochl, J. – Rauch, J.: Matching Data Mining Methods with MetaData and Problem Descriptions in Recommender Systems. In: SNÁŠEL, Václav (ed.). Znalosti 2004 – poster proceedings. Ostrava: VŠB TU, 2004, pp. 65–68.
[SR 02]
Strossa, P. – Rauch, J.: Association Rules in STULONG and Natural Language. In: BERKA, Petr (ed.). ECML/PKDD-2002 Workshop Proceedings: Discovery Challenge Workshop Notes, Report B-2002-8. Helsinki: Universitas Helsingiensis, 2002. ISBN 952-10-0639-0. ISSN 1458-4786.
[SR 03]
Strossa, P. – Rauch, J.: Converting Association Rules into Natural Language. In: KLOPOTEK, M. A., WIERZCHON, S. T., TROJANOWSKI, K. (ed.). IIPWM'03. Berlin: Springer, 2003, pp. 383–392. ISBN 3-540-00843-8.
[So 03]
Štochl, J.: Data mining in catheterization database. In: SVÁTEK, Vojtěch (ed.). Znalosti 2003. Ostrava: TU Ostrava, 2003, pp. 192–201. ISBN 80-248-0229-5. (In Czech)
[St 04]
Strossa, P.: AR2NL/STULONG: an Experiment with a Simple Natural Language Model for Formulating Association Rules. In: SNÁŠEL, Václav (ed.). Znalosti 2004. Ostrava: VŠB TU, 2004, pp. 210–217. ISBN 80-248-0456-5.
[Ze 96]
Zembowicz, R. – Zytkow, J.: From Contingency Tables to Various Forms of Knowledge in Databases. in Fayyad, U. M. et al.: Advances in Knowledge Discovery and Data Mining. AAAI Press/ The MIT Press, 1996. pp. 329–349.

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