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001 978-3-642-11479-3
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005 20140220084530.0
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008 100301s2010 gw | s |||| 0|eng d
020 _a9783642114793
_9978-3-642-11479-3
024 7 _a10.1007/978-3-642-11479-3
_2doi
050 4 _aQA8.9-QA10.3
072 7 _aUYA
_2bicssc
072 7 _aMAT018000
_2bisacsh
072 7 _aCOM051010
_2bisacsh
082 0 4 _a005.131
_223
100 1 _aPeters, James F.
_eeditor.
245 1 0 _aTransactions on Rough Sets XI
_h[electronic resource] /
_cedited by James F. Peters, Andrzej Skowron.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2010.
300 _aIX, 189 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v5946
505 0 _aMining Numerical Data – A Rough Set Approach -- Definability and Other Properties of Approximations for Generalized Indiscernibility Relations -- Variable Consistency Bagging Ensembles -- Classical and Dominance-Based Rough Sets in the Search for Genes under Balancing Selection -- Satisfiability Judgement under Incomplete Information -- Irreducible Descriptive Sets of Attributes for Information Systems -- Computational Theory Perception (CTP), Rough-Fuzzy Uncertainty Analysis and Mining in Bioinformatics and Web Intelligence: A Unified Framework -- Decision Rule-Based Data Models Using TRS and NetTRS – Methods and Algorithms -- A Distributed Decision Rules Calculation Using Apriori Algorithm -- Decision Table Reduction in KDD: Fuzzy Rough Based Approach.
520 _aThe LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. The 10 articles contained in this volume introduce a number of advances in the foundations and applications of rough sets. The topics covered include calculus of attribute-value pairs useful in mining numerical data; definability and coalescence of approximations; a variable consistency generalization approach to bagging, controlled by measures of consistency;the use of classical and dominance-based rough sets in the search for genes; judgement about satisfiability with incomplete information; irreducible descriptive sets of attributes for information systems useful in the design of concurrent data models; computational theory of perceptions (CTP) and its characteristics and relation with fuzzy-granulation; methods and algorithms of Net-processing; and decision table reduction methods based on fuzzy rough sets.
650 0 _aComputer science.
650 0 _aInformation theory.
650 0 _aArtificial intelligence.
650 0 _aComputer vision.
650 0 _aOptical pattern recognition.
650 1 4 _aComputer Science.
650 2 4 _aMathematical Logic and Formal Languages.
650 2 4 _aComputation by Abstract Devices.
650 2 4 _aTheory of Computation.
650 2 4 _aImage Processing and Computer Vision.
650 2 4 _aPattern Recognition.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aSkowron, Andrzej.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642114786
830 0 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v5946
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-11479-3
912 _aZDB-2-SCS
912 _aZDB-2-LNC
999 _c111857
_d111857