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Link to original content: https://doi.org/10.1007/s10707-015-0243-9
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Skyline for geo-textual data

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Abstract

Massive amount of data that are associated with geographic information are generated in Internet. More and more researches focus on how to retrieve geo-textual data effectively. Existing methods mostly allow exact matches for query keywords but fail to support fuzzy preference queries. In this paper, we study the skyline problem of fuzzy preference queries. That is, given a set of geo-textual data, the skyline comprises the objects that are not dominated by others. In this paper, we only consider the problem of two dimensions, the text relevance dimension and the spatial relevance dimension. We introduce two functions to quantify the text relevance and the spatial relevance. We also develop a new index structure to organize the geo-textual data and an algorithm based on it. Theoretical analysis and experimental results show that our method offers scalability and good performance.

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Acknowledgments

This paper was supported by NGFR 973 grant 2012CB316200, NSFC grant 61472099, 61133002 and National Sci-Tech Support Plan 2015BAH10F01.

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Authors and Affiliations

  1. Department of Computer Science and Technology, Harbin Institute of Technology, Harbin, China

    Jianing Li, Hongzhi Wang, Jianzhong Li & Hong Gao

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  1. Jianing Li
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  2. Hongzhi Wang
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  3. Jianzhong Li
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  4. Hong Gao
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Corresponding author

Correspondence to Hongzhi Wang.

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Li, J., Wang, H., Li, J. et al. Skyline for geo-textual data. Geoinformatica 20, 453–469 (2016). https://doi.org/10.1007/s10707-015-0243-9

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