Abstract
The growing production of maps is generating huge volume of data stored in large spatial databases. This huge volume of data exceeds the human analysis capabilities. Spatial data mining methods, derived from data mining methods, allow the extraction of knowledge from these large spatial databases, taking into account the essential notion of spatial dependency. This paper focuses on this specificity of spatial data mining by showing the suitability of join indices to this context. It describes the join index structure and shows how it could be used as a tool for spatial data mining. Thus, this solution brings spatial criteria support to non-spatial information systems.
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Zeitouni, K., Yeh, L., Aufaure, MA. (2001). Join Indices as a Tool for Spatial Data Mining. In: Roddick, J.F., Hornsby, K. (eds) Temporal, Spatial, and Spatio-Temporal Data Mining. TSDM 2000. Lecture Notes in Computer Science(), vol 2007. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45244-3_9
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DOI: https://doi.org/10.1007/3-540-45244-3_9
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