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Spatio-Temporal Data Streams

Part of the book series: SpringerBriefs in Computer Science ((BRIEFSCOMPUTER))

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Abstract

Information flow processing applications need to process a huge volume of continuous data streams. They are pushing traditional database, data warehousing and data mining technologies beyond their limits due to their massively increasing data volumes and demands for real-time processing. This chapter gives an overview of query processing in data stream management systems (DSMS) and the most influential academic prototypes, as well as available commercial products. Furthermore, this chapter also provides an outline of the basic concepts of spatio-temporal knowledge discovery from data streams, including a list of relevant data stream mining academic prototypes and commercial products.

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  1. Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia

    Zdravko Galić

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Galić, Z. (2016). Introduction. In: Spatio-Temporal Data Streams. SpringerBriefs in Computer Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-6575-5_1

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  • DOI: https://doi.org/10.1007/978-1-4939-6575-5_1

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