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Spatial Outlier Detection: Data, Algorithms, Visualizations

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Advances in Spatial and Temporal Databases (SSTD 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6849))

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Abstract

Current Geographic/Geospatial Information Systems (GIS) and Data Mining Systems (DMS) so far are usually not designed to interoperate. GIS research has a strong emphasis on information management and retrieval, whereas DMS usually have too little geographic functionality to perform appropriate analysis. In this demonstration, we introduce an integrated GIS-DMS system for performing advanced data mining tasks such as outlier detection on geo-spatial data, but which also allows the interaction with existing GIS and this way allows a thorough evaluation of the results. The system enables convenient development of new algorithms as well as application of existing data mining algorithms to the spatial domain, bridging the gap between these two worlds.

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Achtert, E., Hettab, A., Kriegel, HP., Schubert, E., Zimek, A. (2011). Spatial Outlier Detection: Data, Algorithms, Visualizations. In: Pfoser, D., et al. Advances in Spatial and Temporal Databases. SSTD 2011. Lecture Notes in Computer Science, vol 6849. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22922-0_41

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  • DOI: https://doi.org/10.1007/978-3-642-22922-0_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22921-3

  • Online ISBN: 978-3-642-22922-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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