Graph-Indexed kNN Query Optimization on Road Network

Author:

Jiang Wei1ORCID,Li Guanyu1,Bai Mei1,Ning Bo1,Wang Xite1,Wei Fangliang1

Affiliation:

1. Faculty of Information Science and Technology, Dalian Maritime University, Dalian 116026, China

Abstract

The nearest neighbors query problem on road networks constitutes a crucial aspect of location-oriented services and has useful practical implications; e.g., it can locate the k-nearest hotels. However, researches who study road networks still encounter obstacles due to the method’s inherent limitations with respect to object mobility. More popular methods employ indexes to store intermediate results to improve querying time efficiency, but these other methods are often accompanied by high time costs. To balance the costs of time and space, a lightweight flow graph index is proposed to reduce the quantity of candidate nodes, and with this index the results of a kNN query can be efficiently obtained. Experiments on real road networks confirm the efficiency and accuracy of our optimized algorithm.

Funder

National Natural Science Foundation of China

genReral scientific research project of Liaoning

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Comparative Analysis of Machine Learning Algorithms for Inflation Rate Classification and Economic Trend Forecasting;Proceedings of the 7th International Conference on Future Networks and Distributed Systems;2023-12-21

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