Spatial co-location pattern discovery without thresholds

Qian, Feng, He, Qinming, Chiew, Kevin and He, Jiangfeng (2012) Spatial co-location pattern discovery without thresholds. Knowledge and Information Systems, 33 (2). pp. 419-445. ISSN 0219-1377

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Spatial co-location pattern mining discovers the subsets of features whose events are frequently located together in geographic space. The current research on this topic adopts a threshold-based approach that requires users to specify in advance the thresholds of distance and prevalence. However, in practice, it is not easy to specify suitable thresholds. In this article, we propose a novel iterative mining framework that discovers spatial co-location patterns without predefined thresholds. With the absolute and relative prevalence of spatial co-locations, our method allows users to iteratively select informative edges to construct the neighborhood relationship graph until every significant co-location has enough confidence and eventually to discover all spatial co-location patterns. The experimental results on real world data sets indicate that our framework is effective for prevalent co-locations discovery.

Item Type: Article
Uncontrolled Keywords: Iterative framework, threshold-free, spatial co-location pattern, prevalence reward
Subjects: G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Ay Okpokam
Date Deposited: 25 Jun 2013 10:12
Last Modified: 13 Oct 2019 00:31

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