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Spatial keyword search: a survey

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Abstract

Spatial keyword search has been playing an indispensable role in personalized route recommendation and geo-textual information retrieval. In this light, we conduct a survey on existing studies of spatial keyword search. We categorize existing works of spatial keyword search based on the types of their input data, output results, and methodologies. For each category, we summarize their common features in terms of input data, output result, indexing scheme, and search algorithms. In addition, we provide detailed description regarding each study of spatial keyword search. This survey summarizes the findings of existing spatial keyword search studies, thus uncovering new insights that may guide software engineers as well as further research.

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Notes

  1. https://www.bing.com/maps/

  2. https://maps.google.com/

  3. https://www.mapquest.com

  4. https://www.bikely.com/

  5. https://www.gps-waypoints.net

  6. https://www.sharemyroutes.com/

  7. https://research.microsoft.com/en-us/projects/geolife/

  8. https://www.twitter.com/

  9. https://www.Facebook.com/

  10. https://www.Foursquare.com/

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  1. UESTC, Chengdu, China

    Lisi Chen & Shuo Shang

  2. Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates

    Chengcheng Yang & Jing Li

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  1. Lisi Chen
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  2. Shuo Shang
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Chen, L., Shang, S., Yang, C. et al. Spatial keyword search: a survey. Geoinformatica 24, 85–106 (2020). https://doi.org/10.1007/s10707-019-00373-y

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