Abstract
Retrieval of textually relevant non-dominated surrounding data objects has many potential applications in spatial databases such as textually relevant nearby point-of-interest retrieval surrounding a user. This paper presents a novel query, called textually-relevant direction-based spatial skyline (TDSS), for retrieving textually relevant non-dominated surrounding data objects in spatial databases. The paper also presents efficient algorithms for processing TDSS queries in spatial databases by designing novel data pruning techniques using keyword inverted index and R-Tree data indexing scheme. The effectiveness and efficiency of the proposed algorithms are demonstrated by conducting extensive experiments.
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Acknowledgement
This work was partially supported by a Griffith University’s 2018 New Researcher Grant with Dr. Md Saiful Islam being the Chief Investigator. The first and second authors contributed equally in this paper.
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Shen, B., Islam, M.S., Taniar, D., Wang, J. (2020). Retrieving Text-Based Surrounding Objects in Spatial Databases. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2019. Advances in Intelligent Systems and Computing, vol 926. Springer, Cham. https://doi.org/10.1007/978-3-030-15032-7_78
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DOI: https://doi.org/10.1007/978-3-030-15032-7_78
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