Spatial outlier detection: Data, algorithms, visualizations

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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. © 2011 Springer-Verlag.

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Achtert, E., Hettab, A., Kriegel, H. P., Schubert, E., & Zimek, A. (2011). Spatial outlier detection: Data, algorithms, visualizations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6849 LNCS, pp. 512–516). https://doi.org/10.1007/978-3-642-22922-0_41

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