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Continuous K-Nearest Neighbor Queries for Moving Objects

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Advances in Computation and Intelligence (ISICA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4683))

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Abstract

Continuous k-nearest neighbors (CKNN) search has been in the core of spatiotemporal database research during the last decade. It is interested in continuously finding the k closest objects to a predefined query object q during a time interval. Existing methods are either computationally intensive performing repetitive queries to the database or restrictive with respect to the application settings. In this paper we develop an efficient method in order to computes CKNN queries for a query point during a specified time interval. The basic advantage of the proposed approach is that only one query is issued per time interval. The R-tree structure is used to index the static objects. An extensive performance evaluation shows that all the techniques we presented boost the query performance greatly.

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Lishan Kang Yong Liu Sanyou Zeng

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© 2007 Springer-Verlag Berlin Heidelberg

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Xiao, H., Li, Q., Sheng, Q. (2007). Continuous K-Nearest Neighbor Queries for Moving Objects. In: Kang, L., Liu, Y., Zeng, S. (eds) Advances in Computation and Intelligence. ISICA 2007. Lecture Notes in Computer Science, vol 4683. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74581-5_49

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  • DOI: https://doi.org/10.1007/978-3-540-74581-5_49

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74580-8

  • Online ISBN: 978-3-540-74581-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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