Skip to main content
SpringerLink
Log in
Book cover

International Joint Conference on Rough Sets

IJCRS 2017: Rough Sets pp 526–539Cite as

Toward Interactive Attribute Selection with Infolattices – A Position Paper

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10314))

Abstract

We discuss a new approach to interactive exploration of high-dimensional data sets which is aimed at building human’s understanding of the data by iterative additions of recommended attributes and objects that can together represent a context in which it may be useful to analyze the data. We identify challenges and expected benefits that our methodology can bring to the users. We also show how our ideas got inspired by Formal Concept Analysis (FCA) and Rough Set Theory (RST). It is though worth emphasizing that this particular paper is not aimed at investigating relationships between FCA and RST. Instead, the goal is to discuss which algorithmic methods developed within FCA and RST could be reused for the purpose of our approach.

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. Guyon, I., Gunn, S., Nikravesh, M., Zadeh, L.A. (eds.): Feature Extraction: Foundations and Applications. Studies in Fuzziness and Soft Computing, vol. 207. Springer, Heidelberg (2006)

    Google Scholar 

  2. Grużdź, A., Ihnatowicz, A., Ślęzak, D.: Interactive gene clustering: a case study of breast cancer microarray data. Inf. Syst. Front. 8(1), 21–27 (2006)

    Article  Google Scholar 

  3. Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning about Data. System Theory, Knowledge Engineering and Problem Solving, vol. 9. Kluwer, Dorchelt (1991)

    Book  MATH  Google Scholar 

  4. Riza, L.S., Janusz, A., Bergmeir, C., Cornelis, C., Herrera, F., Ślęzak, D., Benítez, J.M.: Implementing algorithms of rough set theory and fuzzy rough set theory in the R package “RoughSets”. Inf. Sci. 287, 68–89 (2014)

    Article  Google Scholar 

  5. Suraj, Z., Grochowalski, P.: About new version of RSDS system. Fundam. Informaticae 135(4), 503–519 (2014)

    Google Scholar 

  6. Tunkelang, D.: Faceted Search. Synthesis Lectures on Information Concepts Retrieval, and Services, vol. 1. Morgan & Claypool, San Rafael (2009)

    Google Scholar 

  7. Carpineto, C., Romano, G.: Concept Data Analysis - Theory and Applications. Wiley, Hoboken (2005)

    MATH  Google Scholar 

  8. Poelmans, J., Ignatov, D.I., Kuznetsov, S.O., Dedene, G.: Formal concept analysis in knowledge processing: a survey on applications. Expert Syst. Appl. 40(16), 6538–6560 (2013)

    Article  Google Scholar 

  9. Ślęzak, D., Grzegorowski, M., Janusz, A., Stawicki, S.: Interactive data exploration with infolattices. Abstract Materials of BAFI 2015. http://www.sistemasdeingenieria.cl/BAFI2015/ProceedingsBAFI.pdf

  10. Stumme, G.: On-line analytical processing with conceptual information systems. In: Proceedings of FODO 1998, pp. 117–126 (1998)

    Google Scholar 

  11. Nguyen, S.H., Szczuka, M.: Feature selection in decision systems with constraints. In: Flores, V., et al. (eds.) IJCRS 2016. LNCS, vol. 9920, pp. 537–547. Springer, Cham (2016). doi:10.1007/978-3-319-47160-0_49

    Chapter  Google Scholar 

  12. Stawicki, S., Ślęzak, D., Janusz, A., Widz, S.: Decision bireducts and decision reducts - a comparison. Int. J. Approx. Reason. 84, 75–109 (2017)

    Article  MathSciNet  Google Scholar 

  13. Codocedo, V., Napoli, A.: Formal concept analysis and information retrieval – a survey. In: Baixeries, J., Sacarea, C., Ojeda-Aciego, M. (eds.) ICFCA 2015. LNCS, vol. 9113, pp. 61–77. Springer, Cham (2015). doi:10.1007/978-3-319-19545-2_4

    Chapter  Google Scholar 

  14. Janusz, A., Ślęzak, D., Nguyen, H.S.: Unsupervised similarity learning from textual data. Fundam. Informaticae 119(3–4), 319–336 (2012)

    MathSciNet  MATH  Google Scholar 

  15. Maier, D.: The Theory of Relational Databases. Computer Science Press, Rockville (1983)

    MATH  Google Scholar 

  16. Baixeries, J., Kaytoue, M., Napoli, A.: Characterizing functional dependencies in formal concept analysis with pattern structures. Ann. Math. Artif. Intell. 72(1–2), 129–149 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  17. Ślęzak, D.: Rough sets and functional dependencies in data: foundations of association reducts. In: Gavrilova, M.L., Tan, C.J.K., Wang, Y., Chan, K.C.C. (eds.) Transactions on Computational Science V. LNCS, vol. 5540, pp. 182–205. Springer, Heidelberg (2009). doi:10.1007/978-3-642-02097-1_10

    Google Scholar 

  18. Osman, T., Thakker, D., Schaefer, G.: Utilising semantic technologies for intelligent indexing and retrieval of digital images. Computing 96(7), 651–668 (2014)

    Article  Google Scholar 

  19. Abeel, T., Helleputte, T., de Peer, Y.V., Dupont, P., Saeys, Y.: Robust biomarker identification for cancer diagnosis with ensemble feature selection methods. Bioinformatics 26(3), 392–398 (2010)

    Article  Google Scholar 

  20. Kuncheva, L.I.: Combining Pattern Classifiers: Methods and Algorithms, 2nd edn. Wiley, Hoboken (2014)

    MATH  Google Scholar 

  21. Ganter, B., Wille, R.: Formal Concept Analysis: Mathematical Foundations. Springer, Heidelberg (1998)

    MATH  Google Scholar 

  22. Kaytoue, M., Kuznetsov, S.O., Macko, J., Napoli, A.: Biclustering meets triadic concept analysis. Ann. Math. Artif. Intell. 70(1–2), 55–79 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  23. Díaz, J.C., Medina, J.: Solving systems of fuzzy relation equations by fuzzy property-oriented concepts. Inf. Sci. 222, 405–412 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  24. Dias, S.M., Vieira, N.J.: Concept lattices reduction: definition, analysis and classification. Expert Syst. Appl. 42(20), 7084–7097 (2015)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Informatics, University of Warsaw, ul. Banacha 2, 02-097, Warsaw, Poland

    Dominik Ślęzak, Marek Grzegorowski, Andrzej Janusz & Sebastian Stawicki

Authors
  1. Dominik Ślęzak
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marek Grzegorowski
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Andrzej Janusz
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sebastian Stawicki
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dominik Ślęzak .

Editor information

Editors and Affiliations

  1. Polish-Japanese Academy of Information Technology, Warsaw, Poland

    Lech Polkowski

  2. University of Regina, Regina, Saskatchewan, Canada

    Yiyu Yao

  3. University of Warmia and Mazury, Olsztyn, Poland

    Piotr Artiemjew

  4. University of Milano-Bicocca, Milano, Italy

    Davide Ciucci

  5. Southwest Jiaotong University, Chengdu, China

    Dun Liu

  6. Warsaw University, Warszawa, Poland

    Dominik Ślęzak

  7. Silesian University, Sosnowiec, Poland

    Beata Zielosko

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Ślęzak, D., Grzegorowski, M., Janusz, A., Stawicki, S. (2017). Toward Interactive Attribute Selection with Infolattices – A Position Paper. In: Polkowski, L., et al. Rough Sets. IJCRS 2017. Lecture Notes in Computer Science(), vol 10314. Springer, Cham. https://doi.org/10.1007/978-3-319-60840-2_38

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-60840-2_38

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60839-6

  • Online ISBN: 978-3-319-60840-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation