Skip to main content
SpringerLink
Log in
Book cover

International Conference on Artificial Intelligence: Methodology, Systems, and Applications

AIMSA 2014: Artificial Intelligence: Methodology, Systems, and Applications pp 214–221Cite as

FCA Analyst Session and Data Access Tools in FCART

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8722))

Abstract

Formal Concept Analysis Research Toolbox (FCART) is an integrated environment for knowledge and data engineers with a set of research tools based on Formal Concept Analysis. FCART allows a user to load structured and unstructured data (including texts with various metadata) from heterogeneous data sources into local data storage, compose scaling queries for data snapshots, and then research classical and some innovative FCA artifacts in analytic sessions.

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 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ganter, B., Wille, R.: Formal Concept Analysis: Mathematical Foundations. Springer (1999)

    Google Scholar 

  2. Neznanov, A.A., Ilvovsky, D.A., Kuznetsov, S.O.: FCART: A New FCA-based System for Data Analysis and Knowledge Discovery. Contributions to the 11th International Conference on Formal Concept Analysis, pp. 31–44 (2013)

    Google Scholar 

  3. Mirkin, B.: Mathematical Classification and Clustering. Springer (1996)

    Google Scholar 

  4. Ignatov, D.I., Kuznetsov, S.O., Magizov, R.A., Zhukov, L.E.: From Triconcepts to Triclusters. In: Kuznetsov, S.O., Ślęzak, D., Hepting, D.H., Mirkin, B.G. (eds.) RSFDGrC 2011. LNCS (LNAI), vol. 6743, pp. 257–264. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  5. Kuznetsov, S.O.: Pattern Structures for Analyzing Complex Data. In: Sakai, H., Chakraborty, M.K., Hassanien, A.E., Ślęzak, D., Zhu, W. (eds.) RSFDGrC 2009. LNCS, vol. 5908, pp. 33–44. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  6. Yevtushenko, S.A.: System of data analysis “Concept Explorer”. In: Proceedings of the 7th National Conference on Artificial Intelligence KII 2000, Russia, pp. 127–134 (2000) (in Russian)

    Google Scholar 

  7. Conexp-clj, http://daniel.kxpq.de/math/conexp-clj/

  8. Valtchev, P., Grosser, D., Roume, C., Hacene, M.R.: GALICIA: an open platform for lattices. In: Using Conceptual Structures: Contributions to the 11th Intl. Conference on Conceptual Structures (ICCS 2003), pp. 241–254. Shaker Verlag (2003)

    Google Scholar 

  9. Tockit: Framework for Conceptual Knowledge Processing, http://www.tockit.org

  10. Becker, P., Hereth, J., Stumme, G.: ToscanaJ: An Open Source Tool for Qualitative Data Analysis. In: Proc. Workshop FCAKDD of the 15th European Conference on Artificial Intelligence (ECAI 2002), Lyon, France (2002)

    Google Scholar 

  11. Priss, U.: FcaStone - FCA file format conversion and interoperability software. In: Conceptual Structures Tool Interoperability Workshop, CS-TIW (2008)

    Google Scholar 

  12. Lahcen, B., Kwuida, L.: Lattice Miner: A Tool for Concept Lattice Construction and Exploration. Supplementary Proceeding of International Conference on Formal Concept Analysis, ICFCA 2010 (2010)

    Google Scholar 

  13. Borza, P.V., Sabou, O., Sacarea, C.: OpenFCA, an open source formal concept analysis toolbox. In: Proc. of IEEE International Conference on Automation Quality and Testing Robotics (AQTR), pp. 1–5 (2010)

    Google Scholar 

  14. Szathmary, L.: The Coron Data Mining Platform, http://coron.loria.fr

  15. Cubist Project, http://www.cubist-project.eu/

  16. Web data: Amazon movie reviews, http://snap.stanford.edu/data/web-Movies.html

  17. Poelmans, J., Elzinga, P., Neznanov, A., Viaene. S., Kuznetsov, S.O., Ignatov D., Dedene G.: Concept Relation Discovery and Innovation Enabling Technology (CORDIET). In: Concept Discovery in Unstructured Data. CEUR Workshop proceedings, vol. 757 (2011)

    Google Scholar 

  18. Kuznetsov, S.O., Obiedkov, S., Roth, C.: Reducing the Representation Complexity of Lattice-Based Taxonomies. In: Priss, U., Polovina, S., Hill, R. (eds.) ICCS 2007. LNCS (LNAI), vol. 4604, pp. 241–254. Springer, Heidelberg (2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National Research University Higher School of Economics, Pokrovskiy bd., 11, 109028, Moscow, Russia

    A. A. Neznanov & A. A. Parinov

Authors
  1. A. A. Neznanov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. A. Parinov
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Information and Communication, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Gennady Agre

  2. Department of Computer Science, Wright State University, Dayton, OH, USA

    Pascal Hitzler

  3. Wright State University, Dayton, OH, USA

    Adila A. Krisnadhi

  4. Higher School of Economics, National Research University, Moscow, Russia

    Sergei O. Kuznetsov

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Neznanov, A.A., Parinov, A.A. (2014). FCA Analyst Session and Data Access Tools in FCART. In: Agre, G., Hitzler, P., Krisnadhi, A.A., Kuznetsov, S.O. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2014. Lecture Notes in Computer Science(), vol 8722. Springer, Cham. https://doi.org/10.1007/978-3-319-10554-3_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-10554-3_21

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10553-6

  • Online ISBN: 978-3-319-10554-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation