NDLI: A join-less approach for co-location pattern mining: a summary of results

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A join-less approach for co-location pattern mining: a summary of results

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A join-less approach for co-location pattern mining: a summary of results

Content Provider	IEEE Xplore Digital Library
Author	Jin Soung Yoo Shekhar, Shashi Mete Celik
Copyright Year	2005
Description	Author affiliation: Comput. Sci. Dept., Minnesota Univ., Minneapolis, MN, USA (Jin Soung Yoo; Shashi Shekhar; Mete Celik)
Abstract	Spatial co-location patterns represent the subsets of features whose instances are frequently located together in geographic space. Co-location pattern discovery presents challenges since the instances of spatial features are embedded in a continuous space and share a variety of spatial relationships. A large fraction of the computation time is devoted to identifying the instances of co-location patterns. We propose a novel join-less approach for co-location pattern mining, which materializes spatial neighbor relationships with no loss of co-location instances and reduces the computational cost of identifying the instances. The join-less co-location mining algorithm is efficient since it uses an instance-lookup scheme instead of an expensive spatial or instance join operation for identifying co-location instances. The experimental evaluations show the join-less algorithm performs more efficiently than a current join-based algorithm and is scalable in dense spatial datasets.
File Size	132756
File Format	PDF
ISBN	0769522785
ISSN	15504786
DOI	10.1109/ICDM.2005.8
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-11-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data mining Computational efficiency Birds Association rules Computer science Performance evaluation Geoscience Public healthcare Biology Transportation
Content Type	Text
Resource Type	Article

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