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Approximate Queries for Spatial Data

  • Chapter
Advanced Query Processing

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 36))

Abstract

Approximation techniques for spatial data traditionally concern data capture and data representation issues. On the other hand, more recently developed approximation techniques refer to the query to be executed and not to data representation as in the the past monolithic Geographic Information Systems and for this reason they are called query-based approximation techniques. The aim of this chapter is to survey such approximation techniques and to identify the issues that from our point of view have still to be investigated to complete the picture. In particular, we observe that most of the proposed approaches for spatial approximate queries rely on the usage of quantitative, i.e., metric (distance-based), information. On the other hand, only few of them take into account qualitative information, e.g., topological and cardinal spatial relations. Based on this consideration, we provide new types of queries relying on qualitative relations and we discuss how the query processing algorithms already defined for metric relations can be extended to cope with qualitative information.

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Authors and Affiliations

  1. University of Verona, Verona, Italy

    Alberto Belussi & Sara Migliorini

  2. University of Genoa, Genoa, Italy

    Barbara Catania

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  1. Alberto Belussi
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  2. Barbara Catania
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  3. Sara Migliorini
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Correspondence to Alberto Belussi .

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Editors and Affiliations

  1. Dipto. Informatica e Science, dell'Informazione, Università Genova, Via Dodecaneso 35, Genova, 16146, Italy

    Barbara Catania

  2. , School of Electrical and Information, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, South Australia, Australia

    Lakhmi C. Jain

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Belussi, A., Catania, B., Migliorini, S. (2013). Approximate Queries for Spatial Data. In: Catania, B., Jain, L. (eds) Advanced Query Processing. Intelligent Systems Reference Library, vol 36. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28323-9_5

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  • DOI: https://doi.org/10.1007/978-3-642-28323-9_5

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