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Formal Concept Analysis pp 205–220Cite as

Spatial Indexing for Scalability in FCA

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3874))

Abstract

The paper provides evidence that spatial indexing structures offer faster resolution of Formal Concept Analysis queries than B-Tree/Hash methods. We show that many Formal Concept Analysis operations, computing the contingent and extent sizes as well as listing the matching objects, enjoy improved performance with the use of spatial indexing structures such as the RD-Tree. Speed improvements can vary up to eighty times faster depending on the data and query. The motivation for our study is the application of Formal Concept Analysis to Semantic File Systems. In such applications millions of formal objects must be dealt with. It has been found that spatial indexing also provides an effective indexing technique for more general purpose applications requiring scalability in Formal Concept Analysis systems. The coverage and benchmarking are presented with general applications in mind.

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References

  1. Libferris, http://witme.sourceforge.net/libferris.web/ (visited November 2005)

  2. Mail-sleuth homepage, http://www.mail-sleuth.com/ (visited January 2005)

  3. Postgresql, http://www.postgresql.org/ (visited June 2004)

  4. Blake, C., Merz, C.: UCI Repository of Machine Learning Databases, Irvine, CA. University of California, Department of Information and Computer Science (1998), http://www.ics.uci.edu/~mlearn/MLRepository.html

  5. Carpineto, C., Romano, G.: Concept Data Analysis. Wiley, England (2004)

    Book  MATH  Google Scholar 

  6. Cole, R., Eklund, P.: Analyzing an email collection using formal concept analysis. In: Żytkow, J.M., Rauch, J. (eds.) PKDD 1999. LNCS (LNAI), vol. 1704, pp. 309–315. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  7. Cole, R., Eklund, P.: Browsing semi-structured web texts using formal concept analysis. In: Delugach, H.S., Stumme, G. (eds.) ICCS 2001. LNCS (LNAI), vol. 2120, pp. 319–332. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  8. Cole, R., Stumme, G.: Cem: A conceptual email manager. In: 7th International Conference on Conceptual Structures, ICCS 2000. Springer, Heidelberg (2000)

    Google Scholar 

  9. Folk, M.J., Zoelick, B.: File Structures. Addison-Wesley, Reading (1992)

    MATH  Google Scholar 

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

    MATH  Google Scholar 

  11. Gifford, D.K., Jouvelot, P., Sheldon, M.A., O’Toole Jr., J.W.: Semantic file systems. In: Proceedings of 13th ACM Symposium on Operating Systems Principles, ACM SIGOPS, pp. 16–25 (1991)

    Google Scholar 

  12. Guttman, A.: R-trees: A dynamic index structure for spatial searching. In: Proc. ACM-SIGMOD International Conference on Management of Data, Boston, Mass (1984)

    Google Scholar 

  13. Hellerstein, J.M., Pfeifer, A.: The RD-Tree: An Index Structure for Sets, Technical Report 1252. University of Wisconsin at Madison (October 1994)

    Google Scholar 

  14. Helmer, S.: Index structures for databases containing data items with setvalued attributes (1997)

    Google Scholar 

  15. Martin, B.: File system wide file classiffication with agents. In: Australian Document Computing Symposium (ADCS 2003). University of Queensland (2003)

    Google Scholar 

  16. Martin, B.: Formal concept analysis and semantic file systems. In: Eklund, P. (ed.) ICFCA 2004. LNCS (LNAI), vol. 2961, pp. 88–95. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  17. Zaki, M.J., Parimi, N., De, N., Gao, F., Phoophakdee, B., Urban, J., Chaoji, V., Hasan, M.A., Salem, S.: Towards generic pattern mining. In: Ganter, B., Godin, R. (eds.) ICFCA 2005. LNCS (LNAI), vol. 3403, pp. 1–20. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  18. Kriegelm, H.-P., Schneider, R., Beckmann, N., Seeger, B.: The r*-tree: An efficient and robust access method for points and rectangles. In: Proc. ACM-SIGMOD International Conference on Management of Data, Atlantic city, N.J. (1990)

    Google Scholar 

  19. Padioleau, Y., Ridoux, O.: A logic file system. In: USENIX 2003 Annual Technical Conference, pp. 99–112 (2003)

    Google Scholar 

  20. Prediger, S.: Logical scaling in formal concept analysis. In: International Conference on Conceptual Structures, pp. 332–341. Springer, Heidelberg (1997)

    Google Scholar 

  21. Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., Inkeri Verkamo, A.: Fast discovery of association rules. In: Fayyad, U., et al. (eds.) Advances in Knowledge Discovery and Data Mining, pp. 307–328. AAAI Press, Menlo Park (1996)

    Google Scholar 

  22. Rock, T., Wille, R.: Ein TOSCANA-erkundungssytem zur literatursuche. In: Stumme, G., Wille, R. (eds.) Begriffiche WissensveraRbeitung: Methoden und Anwendungen, pp. 239–253. Springer, Heidelberg (2000)

    Google Scholar 

  23. Stumme, G., Taouil, R., Bastide, Y., Pasquier, N., Lakhal, L.: Computing iceberg concept lattices with titanic. J. on Knowledge and Data Engineering (KDE) 42, 189–222 (2002)

    Article  MATH  Google Scholar 

  24. Tow, D.: SQL Tuning. O’Reilly & Associates, Sebastopol (2004)

    Google Scholar 

  25. Yang, W.S., Chung, Y.D., Kim, M.H.: The rd-tree: a structure for processing partial-max/min queries in olap. Inf. Sci. Appl. 146(1-4), 137–149 (2002)

    Article  MATH  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. Information Technology and Electrical Engineering, The University of Queensland, St. Lucia, QLD 4072, Australia

    Ben Martin

  2. School of Economics and Information Systems, The University of Wollongong, Northfields Avenue, Wollongong, NSW 2522, Australia

    Peter Eklund

Authors
  1. Ben Martin
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  2. Peter Eklund
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Editor information

Editors and Affiliations

  1. Département d’informatique et d’ingénierie, Université du Québec en Outaouais, succursale B, C.P. 1250, J8X 3X7, Gatineau, Québec, Canada

    Rokia Missaoui

  2. Mathematisches Institut, Universität Bern, Sidlerstr. 5, 3012, Bern, Switzerland

    Jürg Schmidt

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© 2006 Springer-Verlag Berlin Heidelberg

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Martin, B., Eklund, P. (2006). Spatial Indexing for Scalability in FCA. In: Missaoui, R., Schmidt, J. (eds) Formal Concept Analysis. Lecture Notes in Computer Science(), vol 3874. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11671404_14

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  • DOI: https://doi.org/10.1007/11671404_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-32203-0

  • Online ISBN: 978-3-540-32204-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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