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020 _a9783540712008
_9978-3-540-71200-8
024 7 _a10.1007/978-3-540-71200-8
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aTransactions on Rough Sets VI
_h[electronic resource] :
_bCommemorating Life and Work of Zdislaw Pawlak, Part I /
_cedited by James F. Peters, Ivo Düntsch, Jerzy Grzymala-Busse, Ewa Orlowska, Lech Polkowski.
250 _a1st ed. 2007.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2007.
300 _aXII, 500 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aTransactions on Rough Sets,
_x1861-2067 ;
_v4374
505 0 _aContributed Papers -- Propositional Logics from Rough Set Theory -- Intuitionistic Rough Sets for Database Applications -- An Experimental Comparison of Three Rough Set Approaches to Missing Attribute Values -- Pawlak’s Landscaping with Rough Sets -- A Comparison of Pawlak’s and Skowron–Stepaniuk’s Approximation of Concepts -- Data Preparation for Data Mining in Medical Data Sets -- A Wistech Paradigm for Intelligent Systems -- The Domain of Acoustics Seen from the Rough Sets Perspective -- Rule Evaluations, Attributes, and Rough Sets: Extension and a Case Study -- The Impact of Rough Set Research in China: In Commemoration of Professor Zdzis?aw Pawlak -- A Four-Valued Logic for Rough Set-Like Approximate Reasoning -- On Representation and Analysis of Crisp and Fuzzy Information Systems -- On Partial Covers, Reducts and Decision Rules with Weights -- A Personal View on AI, Rough Set Theory and Professor Pawlak -- Formal Topology and Information Systems -- On Conjugate Information Systems: A Proposition on How to Learn Concepts in Humane Sciences by Means of Rough Set Theory -- Discovering Association Rules in Incomplete Transactional Databases -- On Combined Classifiers, Rule Induction and Rough Sets -- Approximation Spaces in Multi Relational Knowledge Discovery -- Finding Relevant Attributes in High Dimensional Data: A Distributed Computing Hybrid Data Mining Strategy -- A Model PM for Preprocessing and Data Mining Proper Process -- Monographs -- Lattice Theory for Rough Sets.
650 0 _aArtificial intelligence.
650 0 _aData mining.
650 0 _aComputer science.
650 0 _aMachine theory.
650 0 _aDatabase management.
650 1 4 _aArtificial Intelligence.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aTheory of Computation.
650 2 4 _aFormal Languages and Automata Theory.
650 2 4 _aDatabase Management.
700 1 _aPeters, James F.
_eeditor.
_0(orcid)
_10000-0002-1026-4638
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aDüntsch, Ivo.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aGrzymala-Busse, Jerzy.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aOrlowska, Ewa.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aPolkowski, Lech.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540711988
776 0 8 _iPrinted edition:
_z9783540835998
830 0 _aTransactions on Rough Sets,
_x1861-2067 ;
_v4374
856 4 0 _uhttps://doi.org/10.1007/978-3-540-71200-8
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
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942 _cSPRINGER
999 _c182145
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