Skip to main content
Log in

Hermes: a simple and efficient algorithm for building the AOC-poset of a binary relation

  • Published:
Annals of Mathematics and Artificial Intelligence Aims and scope Submit manuscript

Abstract

Given a relation 𝓡 ⊆ 𝓞 × 𝓐 on a set 𝓞 of objects and a set 𝓐 of attributes, the AOC-poset (Attribute/Object Concept poset), is the partial order defined on the “introducers” of objects and attributes in the corresponding concept lattice. In this paper, we present Hermes, a simple and efficient algorithm for building an AOC-poset which runs in O(m i n{n m, n α}), where n is the number of objects plus the number of attributes, m is the size of the relation, and n α is the time required to perform matrix multiplication (currently α = 2.376). Finally, we compare the runtime of Hermes with the runtime of other algorithms computing the AOC-poset: Ares, Ceres and Pluton. We characterize the cases where each algorithm is the more relevant.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Aboud, N., Arévalo, G., Bendavid, O., Falleri, J.-R., Haderer, N., Huchard, M., Tibermacine, C., Urtado, C., Vauttier, S.: Building hierarchical typed component directories using formal concept analysis. Submitted (2014)

  2. Arévalo, G., Berry, A., Huchard, M., Perrot, G., Sigayret, A.: Performances of Galois sub-hierarchy-building algorithms. In: Kuznetsov, S.O., Schmidt, S. (eds.) ICFCA, Volume 4390 of Lecture Notes in Computer Science, pp 166–180. Springer, Berlin (2007)

    Google Scholar 

  3. Barbut, M., Monjardet, B.: Ordre et Classification – Algèbre et Combinatoire. Hachette, Paris (1970)

    MATH  Google Scholar 

  4. Berry, A., Bordat, J.P., Sigayret, A.: A local approach to concept generation. Ann. Math. Artif. Intell. 49(1–4), 117–136 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  5. Berry, A., Huchard, M., McConnell, R.M., Sigayret, A., Spinrad, J.P.: Efficiently computing a linear extension of the sub-hierarchy of a concept lattice. In: Ganter, B., Godin, R. (eds.) ICFCA, Volume 3403 of Lecture Notes in Computer Science, pp 208–222. Springer, Berlin (2005)

    Google Scholar 

  6. Berry, A., Sigayret, A.: Maintaining class membership information. In: Bruel, J.-M., Bellahsene, Z. (eds.) OOIS Workshops, Volume 2426 of Lecture Notes in Computer Science, pp 13–23. Springer, Berlin (2002)

    Google Scholar 

  7. Bordat, J.P.: Calcul pratique du treillis de Galois d’une correspondance. Math. Inform. Sci. Hum. 96, 31–47 (1986)

    MathSciNet  MATH  Google Scholar 

  8. Coppersmith, D., Winograd, S.: Matrix multiplication via arithmetic progressions. In: Aho, A.V. (ed.) STOC, pp. 1–6. ACM (1987)

  9. Dicky, H., Dony, C., Huchard, M., Libourel, T.: Ares, un algorithme d’ajout avec restructuration dans les hiérarchies de classes. In: Proceedings of LMO’94, pp. 125–136 (1994)

  10. Dicky, H., Dony, C., Huchard, M., Libourel, T.: ARES, adding a class and REStructuring inheritance hierarchies. In: Proceedings of BDA’95, pp. 25–42 (1995)

  11. Dicky, H., Dony, C., Huchard, M., Libourel, T.: On automatic class insertion with overloading. In: Anderson, L., Coplien, J. (eds.) OOPSLA, pp. 251–267. ACM (1996)

  12. Dolques, X., Le Ber, F., Huchard, M.: AOC-Posets: a scalable alternative to concept lattices for relational concept analysis. In: Proceedings of the Tenth International Conference on Concept Lattices and Their Applications (CLA 2013), pp. 129–140 (2013)

  13. Dubois, D., Dupin de Saint Cyr Bannay, F., Prade, H.: A possibilty-theoretic view of formal concept analysis. Fundam. Inform. 75(1–4), 195–213 (2007)

    MATH  Google Scholar 

  14. Dubois, D., Prade, H.: From Blanché’s hexagonal organization of concepts to formal concept analysis and possibility theory. Log. Universalis 6(1–2), 149–169 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  15. Eschen, E.M., Pinet, N., Sigayret, A.: Consecutive-ones: handling lattice planarity efficiently. In: Proceedings of CLA 2007 (Concept Lattices and Applications), CEUR WS, vol. 331, paper 12 (2007)

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

    Book  MATH  Google Scholar 

  17. Godin, R., Mili, H.: Building and maintaining analysis-level class hierarchies using galois lattices. In: Proceedings of OOPSLA ’93, vol. 28, pp. 394–410 (1993)

  18. Godin, R., Mili, H., Mineau, G.W., Missaoui, R., Arfi, A., Chau, T.-T.: Design of class hierarchies based on concept (Galois) lattices. Theory Appl. Object Syst. 4(2), 117–134 (1998)

    Article  Google Scholar 

  19. Hitzler, P.: Default reasoning over domains and concept hierarchies. In: Proceedings of KI 2004, Volume 3238 of LNCS, pp. 351–365. Springer (2004)

  20. Hsu, W.-L., Ma, T.-H.: Fast and simple algorithms for recognizing chordal comparability graphs and interval graphs. SIAM J. Comput. 28(3), 1004–1020 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  21. Huchard, M., Dicky, H., Leblanc, H.: Galois lattice as a framework to specify algorithms building class hierarchies. Theory Inform. Appl. 34, 521–548 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  22. Leblanc, H.: Sous-hiérarchies de Galois: un Modèle pour la Construction et L’évolution des Hiérarchies d’objets (in french). PhD thesis, Université Montpellier II (2000)

  23. Loesch, F., Ploedereder, E.: Restructuring variability in software product lines using concept analysis of product configurations. In: Krikhaar, R.L., Verhoef, C., Lucca, G.A.D. (eds.) Proceedings of the 11th European Conference on Software Maintenance and Reengineering, pp 159–170. IEEE, Amsterdam (2007)

    Google Scholar 

  24. Lubiw, A.: Doubly lexical orderings of matrices. SIAM J. Comput. 16(5), 854–879 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  25. Mineau, G.W., Gecsei, J., Godin, R.: Structuring knowledge bases using automatic learning. In: ICDE, pp. 274–280. IEEE Computer Society (1990)

  26. Osswald, R., Petersen, W.: Induction of classifications from linguistic data. In: Proceedings of ECAI’02 Workshop on Advances in Formal Concept Analysis for Knowledge Discovery in Databases (2002)

  27. Osswald, R., Petersen, W.: A logical approach to data-driven classification. In: Proceedings of the 26th Annual German Conference on Advances in Artificial Intelligence KI 2003, Volume 2821 of LNCS, pp. 267–281. Springer (2003)

  28. Paige, R., Tarjan, R.E.: Three partition algorithms refinement. SIAM J. Comput. 16(6), 973–989 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  29. Petersen, W.: A set-theoretical approach for the induction of inheritance hierarchies. In: Proceedings of the Joint Conference on Formal Grammar and Mathematics of Language (FG/MOL-01), Electronic Notes in Theoretical in Computer Science, vol. 53, pp. 296–308. Elsevier (2001)

  30. Rouane-Hacene, M., Huchard, M., Napoli, A., Valtchev, P.: Relational concept analysis: mining concept lattices from multi-relational data. Ann. Math. Artif. Intell. 67(1), 81–108 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  31. Ryssel, U., Ploennigs, J., Kabitzsch, K.: Extraction of feature models from formal contexts. In: Schaefer, I., John, I., Schmid, K. (eds.) SPLC Workshops, p. 4. ACM (2011)

  32. Sigayret, A.: Data mining: une approche par les graphes (in french). PhD thesis, Université Blaise Pascal (Clermont-Ferrand, France) (2002)

  33. Spinrad, J.P.: Doubly lexical ordering of dense 0-1 matrices. Inf. Process. Lett. 45(5), 229–235 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  34. Spinrad, J.P.: Efficient Graph Representations. American Mathematical Society (AMS), Paris (2003)

    MATH  Google Scholar 

  35. Xue, Y., Xing, Z., Jarzabek, S.: Feature location in a collection of product variants. In: Proceedings of the 19th Working Conference on Reverse Engineering, pp. 145–154. IEEE (2012)

  36. Yang, Y., Peng, X., Zhao, W.: Domain feature model recovery from multiple applications using data access semantics and formal concept analysis. In: Zaidman, A., Antoniol, G., Ducasse, S. (eds.) Proceedings of the 16th Working Conference on Reverse Engineering, pp. 215–224. IEEE (2009)

  37. Yao, Y.: A comparative study of formal concept analysis and rough set theory in data analysis. In: Tsumoto, S., Slowinski, R., Komorowski, H.J., Grzymala-Busse, J.W. (eds.) Rough Sets and Current Trends in Computing, Volume 3066 of Lecture Notes in Computer Science, pp 59–68. Springer, Berlin (2004)

    Google Scholar 

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

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Anne Berry.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Berry, A., Gutierrez, A., Huchard, M. et al. Hermes: a simple and efficient algorithm for building the AOC-poset of a binary relation. Ann Math Artif Intell 72, 45–71 (2014). https://doi.org/10.1007/s10472-014-9418-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10472-014-9418-6

Keywords

Navigation