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International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems

IEA/AIE 2003: Developments in Applied Artificial Intelligence pp 379–384Cite as

SumTime-Turbine: A Knowledge-Based System to Communicate Gas Turbine Time-Series Data

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2718))

Abstract

SumTime-Turbine produces textual summaries of archived time-series data from gas turbines. These summaries should help experts understand large data sets that cannot be visually presented in a single graphical display. SumTime-Turbine is based on pattern detection, knowledge-based temporal abstraction (KBTA), and natural language generation (NLG) technology. A prototype version of the system has been implemented and is currently being evaluated.

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References

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Author information

Authors and Affiliations

  1. Department of Computing Science, University of Aberdeen, Aberdeen, AB24 3UE, UK

    Jin Yu, Ehud Reiter, Jim Hunter & Somayajulu Sripada

Authors
  1. Jin Yu
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  2. Ehud Reiter
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  3. Jim Hunter
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  4. Somayajulu Sripada
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science, Loughborough University, Loughborough, LE11 3TU, England

    Paul W. H. Chung  & Chris Hinde  & 

  2. Dept. of Computer Science, Southwest Texas State University, 601 University Drive, San Marcos, TX, 78666, USA

    Moonis Ali

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© 2003 Springer-Verlag Berlin Heidelberg

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Cite this paper

Yu, J., Reiter, E., Hunter, J., Sripada, S. (2003). SumTime-Turbine: A Knowledge-Based System to Communicate Gas Turbine Time-Series Data. In: Chung, P.W.H., Hinde, C., Ali, M. (eds) Developments in Applied Artificial Intelligence. IEA/AIE 2003. Lecture Notes in Computer Science(), vol 2718. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45034-3_38

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  • DOI: https://doi.org/10.1007/3-540-45034-3_38

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40455-2

  • Online ISBN: 978-3-540-45034-4

  • eBook Packages: Springer Book Archive

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