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Rough Sets and Intelligent Systems Paradigms

International Conference, RSEISP 2007, Warsaw, Poland, June 28-30, 2007. Proceedings

  • Editors
  • Marzena Kryszkiewicz
  • James F. Peters
  • Henryk Rybinski
  • Andrzej Skowron
Conference proceedings RSEISP 2007

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4585)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 4585)

Table of contents

  1. Front Matter
    PDF

  2. Keynote Presentations

    1. Granular Computing and Rough Set Theory
      Lotfi A. Zadeh
      Pages 1-4
    2. Dominance-Based Rough Set Approach to Reasoning About Ordinal Data
      Roman Słowiński, Salvatore Greco, Benedetto Matarazzo
      Pages 5-11

  3. Invited Papers

    1. Mining Numerical Data—A Rough Set Approach
      Jerzy W. Grzymala-Busse
      Pages 12-21
    2. Rough Sets and Approximation Schemes
      Victor W. Marek, Mirosław Truszczynski
      Pages 22-28
    3. Generalizing Data in Natural Language
      Ryszard S. Michalski, Janusz Wojtusiak
      Pages 29-39
    4. Hierarchical Rough Classifiers
      Sinh Hoa Nguyen, Hung Son Nguyen
      Pages 40-50
    5. Discrete Duality and Its Applications to Reasoning with Incomplete Information
      Ewa Orłowska, Ingrid Rewitzky
      Pages 51-56
    6. Toward Approximate Adaptive Learning
      James F. Peters
      Pages 57-68
    7. Granulation of Knowledge in Decision Systems: The Approach Based on Rough Inclusions. The Method and Its Applications
      Lech Polkowski
      Pages 69-79
    8. MIRAI: Multi-hierarchical, FS-Tree Based Music Information Retrieval System
      Zbigniew W. Raś, Xin Zhang, Rory Lewis
      Pages 80-89
    9. Medical Reasoning and Rough Sets
      Shusaku Tsumoto
      Pages 90-100
    10. The Art of Granular Computing
      Yiyu Yao
      Pages 101-112
    11. Dependencies in Structures of Decision Tables
      Wojciech Ziarko
      Pages 113-121

  4. Foundations of Rough Sets

    1. Rough Sets and Vague Sets
      Zbigniew Bonikowski, Urszula Wybraniec-Skardowska
      Pages 122-132
    2. Consistency-Degree Between Knowledges
      M. K. Chakraborty, P. Samanta
      Pages 133-141
    3. On Three Closely Related Rough Inclusion Functions
      Anna Gomolińska
      Pages 142-151
    4. Rough Set Theory from a Math-Assistant Perspective
      Adam Grabowski, Magdalena Jastrzȩbska
      Pages 152-161
    5. Certain, Generalized Decision, and Membership Distribution Reducts Versus Functional Dependencies in Incomplete Systems
      Marzena Kryszkiewicz
      Pages 162-174
    6. On Covering Attribute Sets by Reducts
      Mikhail Ju. Moshkov, Andrzej Skowron, Zbigniew Suraj
      Pages 175-180
    7. Applying Rough Sets to Data Tables Containing Missing Values
      Michinori Nakata, Hiroshi Sakai
      Pages 181-191
    8. Category-Based Rough Induction
      Marcin Wolski
      Pages 192-201
    9. Finding the Reduct Subject to Preference Order of Attributes
      Xiaofeng Zhang, Yongsheng Zhao, Hailin Zou
      Pages 202-210

  5. Foundations and Applications of Fuzzy Sets

    1. Transformation of Fuzzy Takagi-Sugeno Models into Piecewise Affine Models
      Martin Herceg, Michal Kvasnica, Miroslav Fikar
      Pages 211-220
    2. Set Operations for L-Fuzzy Sets
      Jouni Järvinen
      Pages 221-229
    3. Linguistic Summarization of Time Series Under Different Granulation of Describing Features
      Janusz Kacprzyk, Anna Wilbik, Sławomir Zadrożny
      Pages 230-240
    4. Type-2 Fuzzy Summarization of Data: An Improved News Generating
      Adam Niewiadomski
      Pages 241-250

  6. Granular Computing

    1. A Note on Granular Sets and Their Relation to Rough Sets
      Antoni Ligęza, Marcin Szpyrka
      Pages 251-260
    2. Inference and Reformation in Flow Graphs Using Granular Computing
      Huawen Liu, Jigui Sun, Changsong Qi, Xi Bai
      Pages 261-270
    3. On Granular Rough Computing with Missing Values
      Lech Polkowski, Piotr Artiemjew
      Pages 271-279
    4. On Granular Rough Computing: Factoring Classifiers Through Granulated Decision Systems
      Lech Polkowski, Piotr Artiemjew
      Pages 280-289
    5. A Rough Set Based Map Granule
      Sumalee Sonamthiang, Nick Cercone, Kanlaya Naruedomkul
      Pages 290-299
    6. Modeling of High Quality Granules
      Andrzej Skowron, Jaroslaw Stepaniuk
      Pages 300-309

  7. Algorithmic Aspects of Rough Sets

    1. Attribute Core Computation Based on Divide and Conquer Method
      Feng Hu, Guoyin Wang, Ying Xia
      Pages 310-319
    2. Fast Discovery of Minimal Sets of Attributes Functionally Determining a Decision Attribute
      Marzena Kryszkiewicz, Piotr Lasek
      Pages 320-331
    3. A Simple Reduction Analysis and Algorithm Using Rough Sets
      Ning Xu, Yun Zhang, Yongquan Yu
      Pages 332-339

  8. Rough Set Applications (Invited)

    1. Mining Mass Spectrometry Database Search Results—A Rough Set Approach
      Jianwen Fang, Jerzy W. Grzymala-Busse
      Pages 340-349
    2. Rough Set Approach to Spam Filter Learning
      Mawuena Glymin, Wojciech Ziarko
      Pages 350-359
    3. Web-Based Support Systems with Rough Set Analysis
      JingTao Yao, Joseph P. Herbert
      Pages 360-370
    4. Interpreting Low and High Order Rules: A Granular Computing Approach
      Yiyu Yao, Bing Zhou, Yaohua Chen
      Pages 371-380

  9. Rough - Fuzzy Approach

    1. Attribute Reduction Based on Fuzzy Rough Sets
      Degang Chen, Xizhao Wang, Suyun Zhao
      Pages 381-390
    2. On Logic with Fuzzy and Rough Powerset Monads
      Patrik Eklund, Maria A. Galán
      Pages 391-399
    3. A Grey-Rough Set Approach for Interval Data Reduction of Attributes
      Daisuke Yamaguchi, Guo-Dong Li, Masatake Nagai
      Pages 400-410

  10. Information Systems and Rough Sets (Invited)

    1. Minimal Templates and Knowledge Discovery
      Barbara Marszał–Paszek, Piotr Paszek
      Pages 411-416
    2. Universal Attribute Reduction Problem
      Mikhail Ju. Moshkov, Marcin Piliszczuk, Beata Zielosko
      Pages 417-426
    3. Applying Rough Set Theory to Medical Diagnosing
      Piotr Paszek, Alicja Wakulicz–Deja
      Pages 427-435
    4. Graph-Based Knowledge Representations for Decision Support Systems
      Roman Simiński
      Pages 436-444
    5. Rough Sets in Oligonucleotide Microarray Data Analysis
      Magdalena Alicja Tkacz
      Pages 445-453
    6. From an Information System to a Decision Support System
      Alicja Wakulicz–Deja, Agnieszka Nowak
      Pages 454-464

  11. Data and Text Mining

    1. Optimization for MASK Scheme in Privacy Preserving Data Mining for Association Rules
      Piotr Andruszkiewicz
      Pages 465-474

About these proceedings

Keywords

Spam adaptive learning algorithmic learning approximation association mining attribute reducts bioinformatics case-based reasoning classification data mining decision making fuzzy sets machine learning natural language neural network

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-73451-2
  • Copyright Information Springer-Verlag Berlin Heidelberg 2007
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-73450-5
  • Online ISBN 978-3-540-73451-2
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site