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Time-constrained indoor keyword-aware routing: foundations and extensions

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Abstract

With the increasingly available indoor positioning technologies, indoor location-based services (LBS) are becoming popular. Among indoor LBS applications, indoor routing is particularly in demand. In the literature, there are several existing studies on indoor keyword-aware routing queries, each considering different criteria when finding an optimal route. However, none of these studies explicitly constraint the time budget for the route. In this paper, we propose a new problem formulation TIKRQ that considers the time needed for a user to complete the route, in addition to other criteria such as static cost and textual relevance. A set-based search algorithm and effective pruning strategies are proposed as the foundations of processing TIKRQ. To further enhance the practicability of TIKRQ, we study the extensions of TIKRQ and propose efficient solutions. First, we present two TIKRQ variants, namely preferred visiting order and absence of a target point. Second, we present a session-based TIKRQ that keeps track of and refines a user’s routing results when the user changes the query parameters. We conduct extensive experiments on both real and synthetic datasets to verify the efficiency of our proposals.

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Data Availability

The code used and datasets generated during and/or analysed during the current study are available in the GitHub repository, https://github.com/harryckh/TIKRQ.

Notes

  1. https://en.wikipedia.org/wiki/Hong_Kong_International_Airport_Automated_People_Mover

  2. We use a universal walking speed in this paper for ease of illustration, but the proposed method can be easily adapted to the walking speed tailored for partitions.

  3. We do not consider the extreme case that the source and target points are located in the transport, but our technique can easily support it.

  4. Any small value can be used here as long as the original i-word w has a higher score. The routes with w will have higher rankings than those with \(w_{i}^{\prime }\).

  5. https://longaspire.github.io/s/fp.html

  6. https://longaspire.github.io/s/hkdata.html

  7. http://www.keyworddiscovery.com/keyword-stats.html

  8. https://github.com/harryckh/TIKRQ

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Acknowledgments

Huan Li’s work was done with the support of Aalborg University.

Funding

This work was supported by Independent Research Fund Denmark (Grant No. 8022-00366B).

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Authors and Affiliations

  1. Information School, University of Sheffield, Sheffield, UK

    Harry Kai-Ho Chan

  2. Department of People and Technology, Roskilde University, Roskilde, Denmark

    Tiantian Liu & Hua Lu

  3. College of Computer Science and Technology, Zhejiang University, Hangzhou, China

    Huan Li

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  1. Harry Kai-Ho Chan
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  2. Tiantian Liu
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  3. Huan Li
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  4. Hua Lu
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Corresponding author

Correspondence to Harry Kai-Ho Chan.

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Conflict of Interests

Harry Kai-Ho Chan is affiliated to the Information School, University of Sheffield, United Kingdom. Partial of his work was done at the Department of People and Technology, Roskilde University, Denmark. Tiantian Liu and Hua Lu are affiliated to the Department of People and Technology, Roskilde University, Denmark. Huan Li is affiliated to the Department of Computer Science, Aalborg University, Denmark.

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Chan, H.KH., Liu, T., Li, H. et al. Time-constrained indoor keyword-aware routing: foundations and extensions. Geoinformatica 27, 375–426 (2023). https://doi.org/10.1007/s10707-023-00489-2

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