Abstract
In this paper, we study a direction-aware spatial data query method, i.e., range nearest neighbor query with the direction constraint (Range-DCNN query). Traditional DCNN query retrieves the top-k nearest neighbors within an angular range. Our Range-DCNN query finds all nearest neighbors within an angular range for all points in a rectangle. Dissimilar to the traditional DCNN query, the user’s location in the Range-DCNN query is abstracted to a rectangle rather than a point and the user’s location can be anywhere in the rectangle. In doing so, the user’s precise location will not be leaked, which ensures an effective privacy protection of user’s location. In Range-DCNN query, an observation is made that splitting points can be utilized to obtain all query results without having to search for all points. We propose some properties of locating splitting points. According to these properties, efficient algorithms are designed with the assistance of the R-tree. Extensive experiments have been conducted on both real and synthetic datasets. The experimental results demonstrate that our algorithms are capable of locating all results precisely and efficiently.
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Acknowledgment
This work is supported by the National Natural Science Foundation of China (No. 61602031). This work is also supported by Research into the High-Definition Remote Sensing-Based Critical Intelligent Monitoring Technology for Spatial Planning and its Model Applications (Dedicated Project of East-West Cooperation) (No. 2018YBZD1629).
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Miao, X., Guo, X., Yang, X., Wang, Z., Lv, P. (2020). Range Nearest Neighbor Query with the Direction Constraint. In: U, L., Yang, J., Cai, Y., Karlapalem, K., Liu, A., Huang, X. (eds) Web Information Systems Engineering. WISE 2020. Communications in Computer and Information Science, vol 1155. Springer, Singapore. https://doi.org/10.1007/978-981-15-3281-8_11
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DOI: https://doi.org/10.1007/978-981-15-3281-8_11
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