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A segmented parallel expansion algorithm for keyword-aware optimal route query

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Abstract

Keyword-aware Optimal Route Query (KOR) searches for an optimal route with the shortest traveling time under the conditions of full coverage of keywords and route budget, and is a high-frequency query in numerous map applications. Shortening the execution time is the significant goal of KOR optimization. The state-of-the-art algorithms primarily utilize various route expansion approaches to evaluate KORs, and focus on pruning strategies to reduce the search scale and shorten the execution time. Those strategies are effective in controlling the search scale for short routes, however, ineffective for long routes, because the search scale increases exponentially with the search depth. Therefore, this paper proposes PSE-KOR, a segmented parallel expansion algorithm for KOR, to address the issue for long routes. PSE-KOR constructs the routes with keyword vertexes as necessary passing nodes to satisfy the full coverage of keywords and budget, and divides the route into multiple segments taking the keyword vertexes as the boundary to limit the search scale and expands them in parallel to accelerate execution. For each route segment, a local budget limit pruning strategy is proposed to constrain the expansion direction and search depth, while reducing the interference among multiple segments. Extensive experiments verify the efficiency and effectiveness of PSE-KOR.

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Data availability

The datasets generated during and/or analysed during the current study are available in the [9th DIMACS Implementation Challenge—Shortest Paths] competition data, [http://users.diag.uniroma1.it/challenge9/download.shtml].

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Acknowledgements

This work is partially supported by the National Natural Science Foundation of China (Grant No. 62072326), National Key Research and Development Plan of Shanxi Provence (Grant No. 201903D421007).

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Authors and Affiliations

  1. College of Information and Computer, Taiyuan University of Technology, Jinzhong, 030600, Shanxi, China

    Mengmeng Liu, Baoning Niu & Rong Yang

  2. Bank of China Software Center, Xi`an, 710024, Shaanxi, China

    Mengmeng Liu

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  1. Mengmeng Liu
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  2. Baoning Niu
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Correspondence to Baoning Niu.

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.

Baoning Niu reports financial support was provided by National Natural Science Foundation of China. Baoning Niu reports financial support was provided by National Key Research and Development Plan of Shanxi Provence.

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Liu, M., Niu, B. & Yang, R. A segmented parallel expansion algorithm for keyword-aware optimal route query. Geoinformatica 27, 681–707 (2023). https://doi.org/10.1007/s10707-022-00484-z

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  • DOI: https://doi.org/10.1007/s10707-022-00484-z

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