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Efficient moving k nearest neighbor queries over line segment objects

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Abstract

The growing need for location based services motivates the moving k nearest neighbor query (MkNN), which requires to find the k nearest neighbors of a moving query point continuously. In most existing solutions, data objects are abstracted as points. However, lots of real-world data objects, such as roads, rivers or pipelines, should be reasonably modeled as line segments or polyline segments. In this paper, we present LV*-Diagram to handle MkNN queries over line segment data objects. LV*-Diagram dynamically constructs a safe region. The query results remain unchanged if the query point is in the safe region, and hence, the computation cost of the server is greatly reduced. Experimental results show that our approach significantly outperforms the baseline method w.r.t. CPU load, I/O, and communication costs.

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Notes

  1. Fixed-rank means the rank of an object doesn’t change. It is specifically decorate a region (i.e. fixed-ranked region) in our paper, which indicates the ranks of all the objects in such region keep fixed.

  2. Ranking is used to represent the sequence with the objects sorted in this paper. For example, we can say the ranking (of s 1, s 2 and s 3) is 〈s 1, s 3, s 2〉.

  3. The rank of an object means the object’s position in a list of objects sorted by their distances to some other objects.

  4. http://www.chorochronos.org/?q=node/54

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Acknowledgments

This work is supported by the National Basic Research Program of China under Grant No.2012CB316201,the National Natural Science Foundation of China under Grant No.61472071 and 61003058,and the Fundamental Research Funds for the Central Universities of China under Grant No. N130404010.

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  1. Northeastern University, Shenyang, People’s Republic of China

    Yu Gu, Hui Zhang, Zhigang Wang & Ge Yu

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  1. Yu Gu
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  2. Hui Zhang
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  3. Zhigang Wang
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  4. Ge Yu
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Correspondence to Yu Gu.

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Gu, Y., Zhang, H., Wang, Z. et al. Efficient moving k nearest neighbor queries over line segment objects. World Wide Web 19, 653–677 (2016). https://doi.org/10.1007/s11280-015-0351-3

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  • DOI: https://doi.org/10.1007/s11280-015-0351-3

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