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Semantic-aware top-k spatial keyword queries

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Abstract

The fast development of GPS equipped devices has aroused widespread use of spatial keyword querying in location based services nowadays. Existing spatial keyword query methodologies mainly focus on the spatial and textual similarities, while leaving the semantic understanding of keywords in spatial Web objects and queries to be ignored. To address this issue, this paper studies the problem of semantic based spatial keyword querying. It seeks to return the k objects most similar to the query, subject to not only their spatial and textual properties, but also the coherence of their semantic meanings. To achieve that, we propose novel indexing structures, which integrate spatial, textual and semantic information in a hierarchical manner, so as to prune the search space effectively in query processing. Extensive experiments are carried out to evaluate and compare them with other baseline algorithms.

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Authors and Affiliations

  1. School of Computer Science and Technology, Soochow University, Suzhou, China

    Zhihu Qian, Jiajie Xu, Kai Zheng, Pengpeng Zhao & Xiaofang Zhou

  2. School of Information Technology and Electrical Engineering, University of Queensland, St. Lucia, Australia

    Xiaofang Zhou

Authors
  1. Zhihu Qian
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  2. Jiajie Xu
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  3. Kai Zheng
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  4. Pengpeng Zhao
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  5. Xiaofang Zhou
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Correspondence to Jiajie Xu.

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Qian, Z., Xu, J., Zheng, K. et al. Semantic-aware top-k spatial keyword queries. World Wide Web 21, 573–594 (2018). https://doi.org/10.1007/s11280-017-0472-y

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