Skip to main content
SpringerLink
Log in

An Overview of the Deterministic Dynamic Associative Memory (DDAM) Model for Case Representation and Retrieval

  • Conference paper
Case-Based Reasoning Research and Development (ICCBR 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5650))

Included in the following conference series:

  • 806 Accesses

Abstract

The Deterministic Dynamic Associative Memory (DDAM) is a novel associative memory model which generalizes the trie model and addresses the issues of case representation and retrieval. This paper is an overview of the DDAM model outlining its rationale, some of its design principles and its similarities with existing models and approaches. The paper will also report on a selection of experimental results.

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

Access this chapter

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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Knuth, D.E.: Retrieval on Secondary Keys. In: The art of computer programming: Sorting and Searching, pp. 392–559. Addison-Wesley, Reading (1997)

    Google Scholar 

  2. Pantazi, S.V., Arocha, J.F., Moehr, J.R.: Case-based Medical Informatics. BMC Journal of Medical Informatics and Decision Making 4(1) (2004)

    Google Scholar 

  3. Pantazi, S.V., Kushniruk, A., Moehr, J.R.: The usability axiom of medical information systems. International Journal of Medical Informatics 75(12), 829–839 (2006)

    Article  Google Scholar 

  4. Pantazi, S.V.: A Deterministic Dynamic Associative Memory (DDAM) Model for Concept Space Representation, in School of Health Information Science, p. 366. University of Victoria, Victoria (2006), http://hi.conestogac.on.ca/files/dissertation-final.pdf (accessed March 6, 2009)

  5. Pantazi, S.V., Bichindaritz, I., Moehr, J.R.: The case for context-dependent dynamic hierarchical representations of knowledge in Medical Informatics. In: ITCH 2007, Victoria, BC (2007)

    Google Scholar 

  6. Kanerva, P.: Sparse distributed memory. MIT Press, Cambridge (1988); xxii, 155

    MATH  Google Scholar 

  7. Ellard, D., Ellard, P.: S-Q Course Book (2003), http://www.eecs.harvard.edu/~ellard/Courses/ (cited January 24, 2006)

  8. Landauer, T., Dumais, S.: A Solution to Plato’s Problem: The Latent Semantic Analysis Theory of Acquisition, Induction and Representation of Knowledge. Psychological Review 104(2), 211–240 (1997)

    Article  Google Scholar 

  9. Wille, R.: Formal Concept Analysis as Mathematical Theory of Concepts and Concept Hierarchies. In: Ganter, B., Stumme, G., Wille, R. (eds.) Formal Concept Analysis. LNCS, vol. 3626, pp. 1–33. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  10. Erdos, P.L., Sziklai, P., Torney, D.C.: A finite word poset. The Electronic Journal of Combinatorics 8(2), 1–10 (2001)

    MathSciNet  MATH  Google Scholar 

  11. Ventos, V., Soldano, H.: Alpha Galois Lattices: An Overview. In: Ganter, B., Godin, R. (eds.) ICFCA 2005. LNCS, vol. 3403, pp. 299–314. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  12. Díaz-Agudo, B., González Calero, P.A.: Classification based retrieval using formal concept analysis. In: Aha, D.W., Watson, I. (eds.) ICCBR 2001. LNCS, vol. 2080, p. 173. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  13. Bichindaritz, I.: Memory Structures and Organization in Case-based Reasoning. In: Perner, P. (ed.) Case-based Reasoning on Images and Signals, pp. 175–194. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  14. Kohonen, T.: Self-Organizing Maps. In: Huang, T.S. (ed.), 3rd edn. Springer series in information sciences, vol. 30, p. 501. Springer, Heidelberg (2001)

    Google Scholar 

  15. Frick, A., Ludwig, A., Mehldau, H.: A Fast Adaptive Layout Algorithm for Undirected Graphs. In: DIMACS Workshop on Graph Drawing. Springer, Heidelberg (1995)

    Google Scholar 

  16. Knuth, D.E.: The art of computer programming: Sorting and Searching, 2nd edn., vol. 3. Addison-Wesley, Reading (1997)

    MATH  Google Scholar 

  17. Manning, C.D., Schütze, H.: Foundations of Statistical Natural Language Processing, xxxvii, p. 680. MIT Press, Cambridge (1999)

    MATH  Google Scholar 

  18. Bichindaritz, I.: Memory Organization As the Missing Link Between Case Based Reasoning and Information Retrieval in Biomedicine. In: ICCBR 2005 Workshop on CBR in the Health Sciences (2005)

    Google Scholar 

  19. Hersh, W.R., Hickam, D.H., Haynes, B.: A performance and failure analysis with a MEDLINE test collection. J. Am. Med. Inform. Assoc. 1, 51–60 (1994)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Health Sciences, Community Services and Biotechnology, Conestoga College Institute of Technology and Advanced Learning, 299 Doon Valley Drive, Kitchener, ON, Canada, N2G 4M4

    Stefan Pantazi

Authors
  1. Stefan Pantazi
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Adaptive Information Cluster, School of Computer Science & Informatics, University College Dublin,, Computer Science Building, Belfield, Dublin 4, Ireland

    Lorraine McGinty

  2. Department of Software and Information Systems, College of Computing and Informatics, University of North Carolina at Charlotte, 9201 University City Boulevard, NC 28223-0001, Charlotte, USA

    David C. Wilson

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Pantazi, S. (2009). An Overview of the Deterministic Dynamic Associative Memory (DDAM) Model for Case Representation and Retrieval. In: McGinty, L., Wilson, D.C. (eds) Case-Based Reasoning Research and Development. ICCBR 2009. Lecture Notes in Computer Science(), vol 5650. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02998-1_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-02998-1_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02997-4

  • Online ISBN: 978-3-642-02998-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation