Skip to main content

Representing and Recognizing Scenario Patterns

  • Conference paper
Fuzzy Systems and Knowledge Discovery (FSKD 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3614))

Included in the following conference series:

Abstract

This paper presents a formal method for representing and recognizing scenario patterns with rich internal temporal aspects. A scenario is presented as a collection of time-independent fluents, together with the corresponding temporal knowledge that can be relative and/or with absolute values. A graphical representation for temporal scenarios is introduced which supports consistence checking as for the temporal constraints. In terms of such a graphical representation, graph-matching algorithms/methodologies can be directly adopted for recognizing scenario patterns.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. Theodoridis, S., Koutroumbas, K.: Pattern Recognition, 2nd edn. Academic Press, London (2003)

    Google Scholar 

  2. Tveter, D.: The Pattern Recognition Basis of Artificial Intelligence. Wiley-IEEE Computer Society Press (1998)

    Google Scholar 

  3. Knight, B., Ma, J.: A Temporal Database Model Supporting Relative and Absolute Time. the Computer Journal 37(7), 588–597 (1994)

    Article  Google Scholar 

  4. Kahn, M., Gorry, A.: Mechanizing Temporal Knowledge. Artificial Intelligence 9, 87–108 (1977)

    Article  Google Scholar 

  5. Allen, J.: Maintaining knowledge about temporal intervals. Communications of the ACM 26(11), 832–843 (1983)

    Article  MATH  Google Scholar 

  6. Allen, J.: Towards a General Theory of Action and Time. Artificial Intelligence 23, 123–154 (1984)

    Article  MATH  Google Scholar 

  7. Allen, J., Hayes, P.: Moments and Points in an Interval-based Temporal-based Logic. Computational Intelligence 5, 225–238 (1989)

    Article  Google Scholar 

  8. Galton, A.: A Critical Examination of Allen’s Theory of Action and Time. Artificial Intel-ligence 42, 159–188 (1990)

    Article  MATH  MathSciNet  Google Scholar 

  9. Ma, J., Knight, B.: Reified Temporal logic: An Overview. Artificial Intelligence Re-view 15, 189–217 (2001)

    Article  MATH  Google Scholar 

  10. Knight, B., Ma, J.: A General Temporal Model Supporting Duration Reasoning. Artifi-cial Intelligence Communication 5(2), 75–84 (1992)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ma, J., Luo, B. (2005). Representing and Recognizing Scenario Patterns. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11540007_18

Download citation

  • DOI: https://doi.org/10.1007/11540007_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28331-7

  • Online ISBN: 978-3-540-31828-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics