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.
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Sripada, S.G., Reiter, E., Hunter, J., Yu, J. (2003). Segmenting Time Series for Weather Forecasting. In: Macintosh, A., Ellis, R., Coenen, F. (eds) Applications and Innovations in Intelligent Systems X. Springer, London. https://doi.org/10.1007/978-1-4471-0649-4_14
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DOI: https://doi.org/10.1007/978-1-4471-0649-4_14
Publisher Name: Springer, London
Print ISBN: 978-1-85233-673-8
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