rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Rough Sets in Knowledge Discovery 2
    sub title: Applications, Case Studies and Software Systems
  name:
    name part: Polkowski, Lech.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 1998
    edition: 1st ed. 1998.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 601 p. online resource.
  abstract: The papers on rough set theory and its applications placed in this volume present a wide spectrum of problems representative to the present. stage of this theory. Researchers from many countries reveal their rec.ent results on various aspects of rough sets. The papers are not confined only to mathematical theory but also include algorithmic aspects, applications and information about software designed for data analysis based on this theory. The volume contains also list of selected publications on rough sets which can be very useful to every one engaged in research or applications in this domain and sometimes perhaps unaware of results of other authors. The book shows that rough set theory is a vivid and vigorous domain with serious results to its credit and bright perspective for future developments. It lays on the crossroads of fuzzy sets, theory of evidence, neural networks, Petri nets and many other branches of AI, logic and mathematics. These diverse connec­ tions seem to be a very fertile feature of rough set theory and have essentially contributed to its wide and rapid expansion. It is worth mentioning that its philosophical roots stretch down from Leibniz, Frege and Russell up to Popper. Therefore many concepts dwelled on in rough set theory are not entirely new, nevertheless the theory can be viewed as an independent discipline on its own rights. Rough set theory has found many interesting real life applications in medicine, banking, industry and others.
  table of contents: 1. Introducing the Book -- 1. Applications -- 2. Rough Approximation of a Preference Relation in a Pairwise Comparison Table -- 3. Learning Decision Rules from Similarity Based Rough Approximations -- 4. Discovery of Data Patterns with Applications to Decomposition and Classification Problems -- 5. Answering Non-Standard Queries in Distributed Knowledge-Based Systems -- 6. Approximation Spaces, Reducts and Representatives -- 7. Data Mining: A Probabilistic Rough Set Approach -- 2: Case Studies -- 8. Soft Processing of Audio Signals -- 9. A Rough Set Approach to Information Retrieval -- 10. Extraction Method Based on Rough Set Theory of Rule-Type Knowledge from Diagnostic Cases of Slope-Failure Danger Levels -- 11. Soft Computing-Based Recognition of Musical Sounds -- 12. Rough Sets in Industrial Applications -- 13. Rough Sets in Economic Applications -- 14. Multistage Rough Set Analysis of Therapeutic Experience with Acute Pancreatitis -- 15. Reduction Methods for Medical Data -- 16. Formalization and Induction of Medical Expert System Rules Based on Rough Set Theory -- 17. Rough Sets for Database Marketing -- 18. A New Halftoning Method Based on Error Diffusion with Rough Set Filtering -- 3: Hybrid Approaches -- 19. IRIS Revisited: A Comparison of Discriminant and Enhanced Rough Set Data Analysis -- 20. Applications of Rough Patterns -- 21. Time and Clock Information Systems: Concepts and Roughly Fuzzy Petri Net Models -- 22. The Synthesis Problem of Concurrent Systems Specified by Dynamic Information Systems -- 23. Rough Sets and Artificial Neural Networks -- 24. Genetic Algorithms in Decomposition and Classification Problems -- Appendix 1: Rough Set Bibliography -- Selected Bibliography on Rough Sets -- Appendix 2: Software Systems -- GROBIAN -- RSDM: Rough sets Data Miner, A System to Add Data Mining Capabilities to RDBMS -- LERS - A Knowledge Discovery System -- TRANCE: A Tool for Rough Data Analysis, Classification, and Clustering -- ProbRough - A System for P…
  note: edited by Lech Polkowski.
  subject:
    topic: Information technology
  subject:
    topic: Business-Data processing
  subject:
    topic: Artificial intelligence
  subject:
    topic: Database management
  subject:
    topic: IT in Business
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Database Management
  classification: HF54.5-54.56
  classification: 650
  classification: 658.05
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Fuzziness and Soft Computing, 19
  identifier: 9783790818833
  identifier: https://doi.org/10.1007/978-3-7908-1883-3
  record info:
    record creation date: 130220
    record change date: 20191027102533.0
    record identifier: 978-3-7908-1883-3