Skip to main content
SpringerLink
Log in
Book cover

International Joint Conference on Rough Sets

IJCRS 2019: Rough Sets pp 356–368Cite as

Discovering Flow Graphs from Data Tables Using the Classification and Prediction Software System (CLAPSS)

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11499))

Abstract

In the paper, theoretical background, as well as practical implementation, of discovering flow graphs (both fuzzy and rough set) from data tables are presented. We assume that data tables represent information/decision systems in the Pawlak’s sense. The implementation was made in a software tool called the Classification and Prediction Software System (CLAPSS). CLAPSS is a tool developed in the Java technology for solving different classification and prediction problems using, among others, some specialized approaches based mainly on fuzzy sets and rough sets. In general, those specialized approaches implemented in CLAPSS are not available in other tools.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Bazan, J.G., Szczuka, M.: The rough set exploration system. In: Peters, J.F., Skowron, A. (eds.) Transactions on Rough Sets III. LNCS, vol. 3400, pp. 37–56. Springer, Heidelberg (2005). https://doi.org/10.1007/11427834_2

    Chapter  MATH  Google Scholar 

  2. Ellson, J., Gansner, E.R., Koutsofios, E., North, S.C., Woodhull, G.: Graphviz and dynagraph - static and dynamic graph drawing tools. In: Jünger, M., Mutzel, P. (eds.) Graph Drawing Software. MATHVISUAL, pp. 127–148. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-642-18638-7_6

    Chapter  MATH  Google Scholar 

  3. Ford, L.R., Fulkerson, D.: Flows in Networks. Princeton University Press, Princeton (1962)

    MATH  Google Scholar 

  4. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: an update. ACM SIGKDD Explor. Newslett. 11(1), 10–18 (2009)

    Article  Google Scholar 

  5. Kostek, B., Czyzewski, A.: Processing of musical metadata employing Pawlak’s flow graphs. In: Peters, J.F., Skowron, A., Grzymała-Busse, J.W., Kostek, B., Świniarski, R.W., Szczuka, M.S. (eds.) Transactions on Rough Sets I. LNCS, vol. 3100, pp. 279–298. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-27794-1_13

    Chapter  Google Scholar 

  6. Mieszkowicz-Rolka, A., Rolka, L.: Flow graphs and decision tables with fuzzy attributes. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds.) ICAISC 2006. LNCS (LNAI), vol. 4029, pp. 268–277. Springer, Heidelberg (2006). https://doi.org/10.1007/11785231_29

    Chapter  MATH  Google Scholar 

  7. Øhrn, A., Komorowski, J., Skowron, A., Synak, P.: The ROSETTA software system. In: Polkowski, L., Skowron, A. (eds.) Rough Sets in Knowledge Discovery 2, Studies in Fuzziness and Soft Computing, vol. 19, pp. 572–576. Physica-Verlag, Heidelberg (1998)

    MATH  Google Scholar 

  8. Pancerz, K.: On selected functionality of the classification and prediction software system (CLAPSS). In: Proceedings of the International Conference on Information and Digital Technologies (IDT 2015), Zilina, Slovakia, pp. 278–285 (2015)

    Google Scholar 

  9. Pancerz, K., Grochowalski, P., Paja, W.: On selected data preprocessing procedures with the classification and prediction software system (CLAPSS). In: Proceedings of the International Conference on Information and Digital Technologies (IDT 2016), Rzeszow, Poland, pp. 219–226 (2016)

    Google Scholar 

  10. Pancerz, K., Lewicki, A., Tadeusiewicz, R., Warchoł, J.: Ant-based clustering in delta episode information systems based on temporal rough set flow graphs. Fundamenta Informaticae 128(1–2), 143–158 (2013)

    MathSciNet  MATH  Google Scholar 

  11. Pancerz, K.: Paradigmatic and syntagmatic relations in information systems over ontological graphs. Fundamenta Informaticae 148(1–2), 229–242 (2016)

    Article  MathSciNet  Google Scholar 

  12. Pawlak, Z.: Flow graphs and data mining. In: Peters, J.F., Skowron, A. (eds.) Transactions on Rough Sets III. LNCS, vol. 3400, pp. 1–36. Springer, Heidelberg (2005). https://doi.org/10.1007/11427834_1

    Chapter  MATH  Google Scholar 

Download references

Acknowledgments

This work was partially supported by the Center for Innovation and Transfer of Natural Sciences and Engineering Knowledge at the University of Rzeszów.

Author information

Authors and Affiliations

  1. Faculty of Mathematics and Natural Sciences, University of Rzeszów, Pigonia Street 1, 35-310, Rzeszów, Poland

    Krzysztof Pancerz & Jaromir Sarzyński

  2. University of Information Technology and Management in Rzeszów, Sucharskiego Street 2, 35-225, Rzeszów, Poland

    Arkadiusz Lewicki

Authors
  1. Krzysztof Pancerz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Arkadiusz Lewicki
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jaromir Sarzyński
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Krzysztof Pancerz .

Editor information

Editors and Affiliations

  1. University of Debrecen, Debrecen, Hungary

    Tamás Mihálydeák

  2. Southwest Petroleum University, Chengdu, China

    Fan Min

  3. Chongqing University of Posts and Telecommunications, Chongqing, China

    Guoyin Wang

  4. Indian Institute of Technology Kanpur, Kanpur, India

    Mohua Banerjee

  5. Fujian Normal University, Fuzhou, China

    Ivo Düntsch

  6. University of Rzeszów, Rzeszow, Poland

    Zbigniew Suraj

  7. University of Milano-Bicocca, Milan, Italy

    Davide Ciucci

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Pancerz, K., Lewicki, A., Sarzyński, J. (2019). Discovering Flow Graphs from Data Tables Using the Classification and Prediction Software System (CLAPSS). In: Mihálydeák, T., et al. Rough Sets. IJCRS 2019. Lecture Notes in Computer Science(), vol 11499. Springer, Cham. https://doi.org/10.1007/978-3-030-22815-6_28

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-22815-6_28

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22814-9

  • Online ISBN: 978-3-030-22815-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation