Abstract
There has been a vast increase in the amount of spatial data that has become accessible in recent years, mirroring the continuing explosion in information available online. People browsing the Web can download maps of almost any region when planning trips or seeking directions. However, GIS applications generating maps typically present default maps to clients without personalizing any spatial content. This gives rise to a problem whereby the most relevant map information can be obscured by extraneous spatial data, thus hindering users in achieving map interaction goals. Several applications exist that deliver personalized information, but they rely on clients providing explicit input. We describe a novel system that provides personalized map content using techniques prevalent in data mining to model spatial data interaction and to present users with automatically and implicitly personalized map content. Modeling spatial content preferences in this manner allows us to recommend spatial content to individuals whenever they request maps, without requiring the additional burden of explicit user modeling input.
The support of the Informatics Research Initiative of Enterprise Ireland is gratefully acknowledged.
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Weakliam, J., Wilson, D. (2005). Using Data Mining for Modeling Personalized Maps. In: Akoka, J., et al. Perspectives in Conceptual Modeling. ER 2005. Lecture Notes in Computer Science, vol 3770. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11568346_31
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DOI: https://doi.org/10.1007/11568346_31
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