Pattern Structures and Concept Lattices for Data Mining and Knowledge Processing

  • Mehdi KaytoueEmail author
  • Victor Codocedo
  • Aleksey Buzmakov
  • Jaume Baixeries
  • Sergei O. Kuznetsov
  • Amedeo Napoli
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9286)


This article aims at presenting recent advances in Formal Concept Analysis (2010-2015), especially when the question is dealing with complex data (numbers, graphs, sequences, etc.) in domains such as databases (functional dependencies), data-mining (local pattern discovery), information retrieval and information fusion. As these advances are mainly published in artificial intelligence and FCA dedicated venues, a dissemination towards data mining and machine learning is worthwhile.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Alam, M., Buzmakov, A., Codocedo, V., Napoli, A.: An approach for improving RDF data with formal concept analysis. In: Int. Joint Conf. on Artif. Intell. (2015)Google Scholar
  2. 2.
    Assaghir, Z., Napoli, A., Kaytoue, M., Dubois, D., Prade, H.: Numerical information fusion: lattice of answers with supporting arguments. In: Int. Conf. on Tools with Artificial Intelligence (ICTAI), pp. 621–628. IEEE (2011)Google Scholar
  3. 3.
    Baixeries, J., Kaytoue, M., Napoli., A.: Computing similarity dependencies with pattern structures. In: Int. Conf. on Concept Lattices and Their Applications (CLA), CEUR 1062, pp. 33–44 (2013)Google Scholar
  4. 4.
    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)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Buzmakov, A., Egho, E., Jay, N., Kuznetsov, S., Napoli, A., Raïssi, C.: On Mining Complex Sequential Data by Means of FCA and Pattern Structures. International Journal of General Systems (2015)Google Scholar
  6. 6.
    Buzmakov, A., Kuznetsov, S.O., Napoli, A.: Revisiting pattern structure projections. In: Baixeries, J., Sacarea, C., Ojeda-Aciego, M. (eds.) ICFCA 2015. LNCS (LNAI), vol. 9113, pp. 200–215. Springer, Heidelberg (2015) CrossRefGoogle Scholar
  7. 7.
    Codocedo, V., Napoli, A.: Lattice-based biclustering using partition pattern structures. In: European Conf. on Artificial Intelligence (ECAI) (2014)Google Scholar
  8. 8.
    Codocedo, V., Napoli, A.: A proposition for combining pattern structures and relational concept analysis. In: Glodeanu, C.V., Kaytoue, M., Sacarea, C. (eds.) ICFCA 2014. LNCS (LNAI), vol. 8478, pp. 96–111. Springer, Heidelberg (2014) Google Scholar
  9. 9.
    Codocedo, V., Napoli, A.: Formal concept analysis and information retrieval – a survey. In: Baixeries, J., Sacarea, C., Ojeda-Aciego, M. (eds.) ICFCA 2015. LNCS (LNAI), vol. 9113, pp. 61–77. Springer, Heidelberg (2015) CrossRefGoogle Scholar
  10. 10.
    Ganter, B., Kuznetsov, S.O.: Pattern structures and their projections. In: Delugach, H.S., Stumme, G. (eds.) ICCS 2001. LNCS (LNAI), vol. 2120, pp. 129–142. Springer, Heidelberg (2001) CrossRefGoogle Scholar
  11. 11.
    Ganter, B., Wille, R.: Formal Concept Analysis. Springer, Berlin (1999)CrossRefGoogle Scholar
  12. 12.
    Kaytoue, M., Assaghir, Z., Napoli, A., Kuznetsov, S.O.: Embedding tolerance relations in fca: an application in information fusion. In: CIKM. ACM (2010)Google Scholar
  13. 13.
    Kaytoue, M., Kuznetsov, S.O., Macko, J., Napoli, A.: Biclustering meets triadic concept analysis. Ann. Math. Artif. Intell. 70(1–2), 55–79 (2014)MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    Kaytoue, M., Kuznetsov, S.O., Napoli, A.: Biclustering numerical data in formal concept analysis. In: Jäschke, R. (ed.) ICFCA 2011. LNCS (LNAI), vol. 6628, pp. 135–150. Springer, Heidelberg (2011) CrossRefGoogle Scholar
  15. 15.
    Kaytoue, M., Kuznetsov, S.O., Napoli, A.: Revisiting numerical pattern mining with formal concept analysis. In: Int. Joint Conf. on Art. Intell. (IJCAI) (2011)Google Scholar
  16. 16.
    Kaytoue, M., Kuznetsov, S.O., Napoli, A., Duplessis, S.: Mining gene expression data with pattern structures in formal concept analysis. Inf. Sci. 181(10) (2011)Google Scholar
  17. 17.
    Kuznetsov, S.O.: Galois connections in data analysis: contributions from the soviet era and modern russian research. In: Ganter, B., Stumme, G., Wille, R. (eds.) Formal Concept Analysis. LNCS (LNAI), vol. 3626, pp. 196–225. Springer, Heidelberg (2005) CrossRefGoogle Scholar
  18. 18.
    Kuznetsov, S.O.: Learning of simple conceptual graphs from positive and negative examples. In: Żytkow, J.M., Rauch, J. (eds.) PKDD 1999. LNCS (LNAI), vol. 1704, pp. 384–391. Springer, Heidelberg (1999) CrossRefGoogle Scholar
  19. 19.
    Kuznetsov, S.O.: Fitting pattern structures to knowledge discovery in big data. In: Cellier, P., Distel, F., Ganter, B. (eds.) ICFCA 2013. LNCS (LNAI), vol. 7880, pp. 254–266. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  20. 20.
    Kuznetsov, S.O., Poelmans, J.: Knowledge representation and processing with formal concept analysis. Wiley Interdisc. Rew.: Data Mining and Knowledge Discovery 3(3), 200–215 (2013)Google Scholar
  21. 21.
    Kuznetsov, S.O., Samokhin, M.V.: Learning closed sets of labeled graphs for chemical applications. In: Kramer, S., Pfahringer, B. (eds.) ILP 2005. LNCS (LNAI), vol. 3625, pp. 190–208. Springer, Heidelberg (2005) CrossRefGoogle Scholar
  22. 22.
    Leeuwenberg, A., Buzmakov, A., Toussaint, Y., Napoli, A.: Exploring pattern structures of syntactic trees for relation extraction. In: Baixeries, J., Sacarea, C., Ojeda-Aciego, M. (eds.) ICFCA 2015. LNCS (LNAI), vol. 9113, pp. 153–168. Springer, Heidelberg (2015) CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Mehdi Kaytoue
    • 1
    Email author
  • Victor Codocedo
    • 1
  • Aleksey Buzmakov
    • 2
  • Jaume Baixeries
    • 3
  • Sergei O. Kuznetsov
    • 4
  • Amedeo Napoli
    • 2
  1. 1.Université de Lyon, CNRS, INSA-Lyon, LIRIS, UMR5205LyonFrance
  2. 2.LORIA (CNRS - Inria Nancy Grand Est - Université de Lorraine)Vandœuvre-lès-NancyFrance
  3. 3.Universitat Politècnica de CatalunyaBarcelonaSpain
  4. 4.National Research University Higher School of Economics (HSE)MoscowRussia

Personalised recommendations