Citation

Zhang Z, Yang S, Qin Y, Yang Z, Huang Y, Zhou X. Neural Comput Appl 2022; ePub(ePub): ePub.

Copyright

(Copyright © 2022, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s00521-022-07485-x

PMID

35789916

PMCID

PMC9244333

Abstract

Graphs are widespread in many real-life practical applications. One of a graph's fundamental and popular researches is investigating the relations between two given vertices. The relationship between nodes in the graph can be measured by the shortest distance. Moreover, the number of paths is also a popular metric to assess the relationship of different nodes. In many location-based services, users make decisions on the basis of both the two metrics. To address this problem, we propose a new hybrid-metric based on the number of paths with a distance constraint for road networks, which are special graphs. Based on it, a most relevant node query on road networks is identified. To handle this problem, we first propose a Shortest-Distance Constrained DFS, which uses the shortest distance to prune unqualified nodes. To further improve query efficiency, we present Batch Query DFS algorithm, which only needs only one DFS search. Our experiments on four real-life road networks demonstrate the performance of the proposed algorithms.

Language: en

Keywords

Road networks; Graph; Path enumeration; Relevant vertices