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Encyclopedia of Database Systems pp 3627–3633Cite as

Spatial-Keyword Search

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Synonyms

Spatial-keyword query processing; Top-k spatial-keyword search

Definition

Consider a set of spatial-textual objects where each object consists of a spatial location and a textual description. A spatial-keyword search retrieves objects of interest based on both spatial proximity to the query location and the textual relevance to the query keywords. Typically, the spatial proximity is based on distance, while the textual similarity is measured using an information retrieval model such as the cosine similarity or the language model. Query answers are usually ranked based on a linear combination of the two aspects. The goal of spatial-keyword query processing is to return the relevant answers while minimizing the processing cost.

Historical Background

Web content has traditionally been queried using keyword search. More recently, the web has taken on a new dimension – the spatial dimension. On one hand, the prevalence of GPS-enabled smartphones and social network systems has...

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Recommended Readings

  1. Cong G, Jensen CS, Efficient DW. Retrieval of the top-k most relevant spatial web objects. Proc VLDB Endow. 2009;2(1):337–48.

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  2. Li Z, Lee K, ZHeng B, Lee W, Lee D, Wang X. IR-tree: an efficient index for geographic document search. IEEE Trans Knowl Data Eng. 2011;23(4):585–99.

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  3. Chen L, Cong G, Jensen CS, Wu D. Spatial keyword query processing: an experimental evaluation. Proc VLDB Endow. 2013;6(3):217–28.

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  4. Rocha-Junior JB, Gkorgkas O, Jonassen S, Nørvag K. Efficient processing of top-k spatial keyword queries. In: Proceedings of the 12th International Symposium on Spatial and Temporal Databases; 2011. p. 205–22.

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  5. Zhang D, Tan KL, Tung AKH. Scalable top-k spatial keyword search. In: Proceedings of the 16th International Conference on Extending Database Technology; 2013. p. 359–70.

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  6. Zhang D, Chan CY, Tan KL. Processing spatial keyword query as a top-k aggregation query. In: Proceedings of the 34th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval; 2014. p. 355–64.

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  7. Fagin R, Lotem A, Naor M. Optimal aggregation algorithms for middleware. J Comput Syst Sci. 2003;66(4):614–56.

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  8. Huang W, Li G, Tan KL, Feng J. Efficient safe-region construction for moving top-k spatial keyword queries. In: Proceedings of the 21st ACM International Conference on Information and Knowledge Management; 2012. p. 932–41.

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  9. Rocha-Junior JB, Nørvag K. Top-k spatial keyword queries on road networks. In: Proceedings of the 15th International Conference on Extending Database Technology; 2012. p. 168–79.

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  10. Guo L, Shao J, Aung HH, Tan KL. Efficient continuous top-k spatial keyword queries on road networks. GeoInformatica. 2015;19(1):29–60.

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  11. Hu H, Liu Y, Li G, Feng J, Tan KL. A location-aware publish/subscribe framework for parameterized Spatio-textual subscriptions. In: Proceedings of the 31st International Conference on Data Engineering; 2015. p. 711–22.

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  13. Guo L, Zhang D, Li G, Tan KL, Bao Z. Location-aware pub/sub system: when continuous moving queries meet dynamic event streams. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; p. 843–57.

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Author information

Authors and Affiliations

  1. Department of Computer Science, National University of Singapore, Singapore, Singapore

    Kian-Lee Tan

Authors
  1. Kian-Lee Tan
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Corresponding author

Correspondence to Kian-Lee Tan .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

Section Editor information

  1. Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong, Hong Kong SAR

    Dimitris Papadias

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Tan, KL. (2018). Spatial-Keyword Search. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_80661

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