Optimal location query based on k nearest neighbours

Abstract

Optimal location query in road networks is a basic operation in the location intelligence applications. Given a set of clients and servers on a road network, the purpose of optimal location query is to obtain a location for a new server, so that a certain objective function calculated based on the locations of clients and servers is optimal. Existing works assume no labels for servers and that a client only visits the nearest server. These assumptions are not realistic and it renders the existing work not useful in many cases. In this paper, we relax these assumptions and consider the k nearest neighbours (KNN) of clients. We introduce the problem of KNN-based optimal location query (KOLQ) which considers the k nearest servers of clients and labeled servers. We also introduce a variant problem called relocation KOLQ (RKOLQ) which aims at relocating an existing server to an optimal location. Two main analysis algorithms are proposed for these problems. Extensive experiments on the real road networks illustrate the efficiency of our proposed solutions.

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Acknowledgements

We would like to thank all the anonymous reviewers for their insightful and helpful comments. This paper was supported by the National Nature Science Foundation of China (Grant Nos. 61572537, U1501252).

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Corresponding author

Correspondence to Yubao Liu.

Additional information

The initial version of this work has been included in the proceedings of MDM 2019 as a regular research paper [15]

Yubao Liu is currently a professor with the Department of Computer Science of Sun Yat-Sen University, China. He received his PhD in computer science from Huazhong University of Science and Technology, China in 2003. He has published more than 50 refereed journal and conference papers including SIGMOD, TODS, VLDB and VLDBJ, etc. His research interests include database systems and data mining. He is a senior member of the China Computer Federation (CCF).

Zitong Chen is currently working towards the PhD degree in the Department of Computer Science and Engineering, the Chinese University of Hong Kong, China. His research interests include database, data mining, and machine learning.

Ada Wai-Chee Fu received her BSc degree in computer science in the Chinese University of Hong Kong, China in 1983, and both MSc and PhD degrees in Computer Science in Simon Fraser University of Canada in 1986, 1990, respectively; worked at Bell Northern Research in Ottawa, Canada from 1989 to 1993; joined the Chinese University of Hong Kong, China in 1993.

Raymond Chi-Wing Wong is an associate professor in Computer Science and Engineering (CSE) of The Hong Kong University of Science and Technology (HKUST), China. He is currently the associate director of the Data Science and Technology (DSCT) program. He was the director of the Risk Management and Business Intelligence (RMBI) program from 2017 to 2019, the director of the Computer Engineering (CPEG) program from 2014 to 2016 and was the associate director of the Computer Engineering (CPEG) program from 2012 to 2014. He received the BSc, MPhil and PhD degrees in Computer Science and Engineering in the Chinese University of Hong Kong (CUHK), China in 2002, 2004 and 2008, respectively.

Genan Dai is currently working towards the PhD degree in the School of Data and Computer Science, Sun Yat-Sen University, China. Her research interests include data mining and artificial intelligence.

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Liu, Y., Chen, Z., Fu, A.WC. et al. Optimal location query based on k nearest neighbours. Front. Comput. Sci. 15, 152606 (2021). https://doi.org/10.1007/s11704-020-9279-6

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Keywords

  • optimal location query
  • k nearest neighbours
  • road network