Abstract
Spatial co-location patterns represent the subsets of spatial features whose instances are frequently located together in geographic space. Common frameworks for mining co-location patterns generate numerous redundant co-location patterns. Thus, several methods were proposed to overcome this drawback. However, most of these methods do not guarantee that the extracted co-location patterns are interesting for the user because they are generally based on statistical information. Thus, it is crucial to help the decision-maker choose interesting co-location patterns with an efficient interactive procedure. This paper proposed an interactive approach to prune and filter discovered co-location patterns. First, ontologies were used to improve the integration of user knowledge. Second, an interactive process was designed to collaborate with the user to find the interesting co-location patterns efficiently. The experimental results on a real data set demonstrated the effectiveness of our approach.
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Acknowledgements
This work was supported in part by grants (No. 61472346, No. 61262069) from the National Natural Science Foundation of China and in part by a grant (No. 2016FA026, No. 2015FB149, and No. 2015FB114) from the Science Foundation of Yunnan Province.
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Bao, X., Wang, L., Chen, H. (2016). Ontology-Based Interactive Post-mining of Interesting Co-location Patterns. In: Li, F., Shim, K., Zheng, K., Liu, G. (eds) Web Technologies and Applications. APWeb 2016. Lecture Notes in Computer Science(), vol 9932. Springer, Cham. https://doi.org/10.1007/978-3-319-45817-5_35
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DOI: https://doi.org/10.1007/978-3-319-45817-5_35
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