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IRSJ: incremental refining spatial joins for interactive queries in GIS

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Abstract

An increasing number of emerging web database applications deal with large georeferenced data sets. However, exploring these large data sets through spatial queries can be very time and resource intensive. The need for interactive spatial queries has arisen in many applications such as Geographic Information Systems (GIS) for efficient decision-support. In this paper, we propose a new interactive spatial query processing technique for GIS. We present a family of the Incremental Refining Spatial Join (IRSJ) algorithms that can be used to report incrementally refined running estimates for aggregate queries while simultaneously displaying the actual query result tuples of the data sets sampled so far. Our goal is to minimize the time until an acceptably accurate estimate of the query result is available (to users) measured by a confidence interval. Our approach enables more interactive data exploration and analysis. While similar work has been done in relational databases, to the best of our knowledge, this is the first work using this approach in GIS. We investigate and evaluate different sampling methodologies through extensive experimental performance comparisons. Experiments on both real and synthetic data show an order of magnitude response time improvement relative to the final answer obtained when using a full R-tree join. We also show the impact of different index structures on the performance of our algorithms using three known sampling methods.

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Acknowledgements

The following people provided helpful suggestions during early stages of this work: Dr. Sada Narayanappa, Brandon Haenlein, and Mohammed Albow. Help in statistics was graciously provided by Dr. Petr Vojtěchovský.

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Authors and Affiliations

  1. Department of Mathematics, Statistics and Computer Science, University of Wisconsin-Stout, Menomonie, WI, USA

    Wan D. Bae

  2. College of Information Technology, United Arab Emirates University, Al-Ain, United Arab Emirates

    Shayma Alkobaisi

  3. Department of Computer Science, University of Denver, Denver, CO, 80208, USA

    Scott T. Leutenegger

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  1. Wan D. Bae
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  2. Shayma Alkobaisi
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  3. Scott T. Leutenegger
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Correspondence to Wan D. Bae.

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Bae, W.D., Alkobaisi, S. & Leutenegger, S.T. IRSJ: incremental refining spatial joins for interactive queries in GIS. Geoinformatica 14, 507–543 (2010). https://doi.org/10.1007/s10707-009-0089-0

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