Rough Sets and Knowledge Technology

4th International Conference, RSKT 2009, Gold Coast, Australia, July 14-16, 2009. Proceedings

ISBN: 978-3-642-02961-5 (Print) 978-3-642-02962-2 (Online)

Table of contents (88 chapters)

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  1. Front Matter

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  2. Keynote Papers

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      Pages 1-16

      Interactive Granular Computing in Rightly Judging Systems

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      Pages 17-26

      Rough Diamonds in Natural Language Learning

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      Pages 27-29

      KT: Knowledge Technology — The Next Step of Information Technology (IT)

  3. Rough Sets and Computing

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      Pages 30-37

      Rough 3-Valued Łukasiewicz Agebras and MV-Algebras

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      Pages 38-45

      Mechanisms of Partial Supervision in Rough Clustering Approaches

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      Pages 46-51

      Lattice Derived by Double Indiscernibility and Computational Complementarity

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      Pages 52-59

      Double Approximation and Complete Lattices

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      Pages 60-67

      Integrating Rough Sets with Neural Networks for Weighting Road Safety Performance Indicators

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      Pages 68-75

      Evolutionary Rough K-Means Clustering

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      Pages 76-85

      Rough Sets under Non-deterministic Information

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      Pages 86-93

      Development of the Data Preprocessing Agent’s Knowledge for Data Mining Using Rough Set Theory

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      Pages 94-101

      Improving Rules Quality Generated by Rough Set Theory for the Diagnosis of Students with LDs through Mixed Samples Clustering

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      Pages 102-110

      Topological Residuated Lattice: A Unifying Algebra Representation of Some Rough Set Models

  4. Rough Sets and Data Reduction

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      Pages 111-119

      A Time-Reduction Strategy to Feature Selection in Rough Set Theory

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      Pages 120-127

      Reducts Evaluation Methods Using Lazy Algorithms

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      Pages 128-135

      Knowledge Reduction in Formal Contexts Based on Covering Rough Sets

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      Pages 136-143

      On New Concept in Computation of Reduct in Rough Sets Theory

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      Pages 144-151

      Research of Knowledge Reduction Based on New Conditional Entropy

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      Pages 152-159

      Research on Complete Algorithms for Minimal Attribute Reduction

  5. Data Mining and Knowledge Discovery

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      Pages 160-167

      A Comparison of Composed Objective Rule Evaluation Indices Using PCA and Single Indices

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