Distributed algorithm for computing formal concepts using map-reduce framework

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5772 LCNS, Issue , 2009, Pages 333-344

  Krajca, Petr ^a,b   Vychodil, Vilem ^a,b  

^a BINGHAMTON UNIVERSITY   (United States)

^b PALACKÝ UNIVERSITY   (Czech Republic)

Author keywords

[No Author keywords available]

Indexed keywords

BINARY MATRIX; DISTRIBUTED ALGORITHM; FORMAL CONCEPT ANALYSIS; FORMAL CONCEPTS; SMALL DATA SET;

COMPUTATIONAL COMPLEXITY; COMPUTER SCIENCE; PARALLEL ALGORITHMS;

DATA PROCESSING;

EID: 70349886465     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-03915-7_29     Document Type: Conference Paper

References (19)

1. Belohlavek, R., Vychodil, V.: Discovery of optimal factors in binary data via a novel method of matrix decomposition. Journal of Computer and System Sciences (to appear
2. Berry, A., Bordat, J.-P., Sigayret, A.: A local approach to concept generation. Annals of Mathematics and Artificial Intelligence 49, 117-136 (2007
3. Carpineto, C., Romano, G.: Concept data analysis. Theory and applications. J. Wiley, Chichester (2004
4. Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. Commun. ACM 51(1), 107-113 (2008
5. Fu, H., Nguifo, E.M.: A parallel algorithm to generate formal concepts for large data. In: Eklund, P. (ed.) ICFCA 2004. LNCS (LNAI), vol.2961, pp. 394-401. Springer, Heidelberg (2004
6. Ganter, B.: Two basic algorithms in concept analysis (Technical Report FB4- Preprint No. 831). TH Darmstadt (1984
7. Ganter, B., Wille, R.: Formal concept analysis. Mathematical foundations. Springer, Berlin (1999
8. Hadoop Core Framework, http://hadoop.apache.org/
9. Hettich, S., Bay, S.D.: The UCI KDD Archive University of California, Irvine, School of Information and Computer Sciences (1999
10. Kengue, J.F.D., Valtchev, P., Djamegni, C.T.: A parallel algorithm for lattice construction. In: Ganter, B., Godin, R. (eds.) ICFCA 2005. LNCS (LNAI), vol.3403, pp. 249-264. Springer, Heidelberg (2005
11. Miettinen, P., Mielikäinen, T., Gionis, A., Das, G., Mannila, H.: The discrete basis problem. In: Fürnkranz, J., Sche.er, T., Spiliopoulou, M. (eds.) PKDD 2006. LNCS (LNAI), vol.4213, pp. 335-346. Springer, Heidelberg (2006
12. Krajca, P., Outrata, J., Vychodil, V.: Parallel Recursive Algorithm for FCA. In: Belohlavek, R., Kuznetsov, S.O. (eds.) Proc. CLA 2008, vol.433, pp. 71-82. CEUR WS (2008) ISBN 978-80-244-2111-7
13. Krajca, P., Outrata, J., Vychodil, V.: Parallel Algorithm for Computing Fixpoints of Galois Connections. Annals of Mathematics and Artificial Intelligence (submitted
14. Kuznetsov, S.: Interpretation on graphs and complexity characteristics of a search for specific patterns. Automatic Documentation and Mathematical Linguistics 24(1), 37-45 (1989
15. Kuznetsov, S.: A fast algorithm for computing all intersections of objects in a .- nite semi-lattice (Bystry-i algoritm postroeni- vseh pereseqeni-i ob-ektov iz koneqno-i polurexetki, in Russian). Automatic Documentation and Mathematical Linguistics 27(5), 11-21 (1993
16. Kuznetsov, S.O.: Learning of simple conceptual graphs from positive and negative examples. In: Zytkow, J.M., Rauch, J. (eds.) PKDD 1999. LNCS (LNAI), vol.1704, pp. 384-391. Springer, Heidelberg (1999
17. Kuznetsov, S., Obiedkov, S.: Comparing performance of algorithms for generating concept lattices. J. Exp. Theor. Artif. Int. 14, 189-216 (2002
18. Lindig, C.: Fast concept analysis. In: Working with Conceptual Structures -- Contributions to ICCS 2000, pp. 152-161. Shaker Verlag, Aachen (2000
19. Wille, R.: Restructuring lattice theory: an approach based on hierarchies of concepts. In: Ordered Sets, Dordrecht, Boston, pp. 445-470 (1982