Segmenting time series for weather forecasting

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We are investigating techniques for producing textual summaries of time series data. Deep reasoning techniques have proven impractical because we lack perfect knowledge about users and their tasks. Data analysis techniques such as segmentation are more attractive, but they have been developed for data mining, not for communication. We examine how segmentation should be modified to make it suitable for generating textual summaries. Our algorithm has been implemented in a weather forecast generation system.

Original languageEnglish
Title of host publicationApplications and Innovations in Intelligent Systems X
EditorsAnn Macintosh, Richard Ellis, Frans Coenen
PublisherSpringer
Pages193-206
Number of pages14
ISBN (Print) 978-1-85233-673-8
Publication statusPublished - 2003
EventTwenty-second SGAI International Conference on Knowledge Based Systems and Applied Artificial Intelligence - Cambridge, United Kingdom
Duration: 1 Dec 2002 → …

Conference

ConferenceTwenty-second SGAI International Conference on Knowledge Based Systems and Applied Artificial Intelligence
CountryUnited Kingdom
CityCambridge
Period1/12/02 → …

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  • Cite this

    Sripada, S. G., Reiter, E. B., Hunter, J., & Yu, J. (2003). Segmenting time series for weather forecasting. In A. Macintosh, R. Ellis, & F. Coenen (Eds.), Applications and Innovations in Intelligent Systems X (pp. 193-206). Springer .