A learned spatial textual index for efficient keyword queries-Reference-Cited by-同舟云学术

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A learned spatial textual index for efficient keyword queries

Published:2022-10-13 Issue: Volume: Page:
ISSN:0925-9902
Container-title:Journal of Intelligent Information Systems
language:en
Short-container-title:J Intell Inf Syst

Author:

Ding Xiaofeng,Zheng Yinting,Wang Zuan,Choo Kim-Kwang Raymond,Jin Hai

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture,Information Systems,Software

Link

https://link.springer.com/content/pdf/10.1007/s10844-022-00752-2.pdf

Reference41 articles.

1. Aref, W. G., & Ilyas, I. F. (2001). Sp-gist: An extensible database index for supporting space partitioning trees. Journal of Intelligent Information Systems, 17(2–3), 215–240. https://doi.org/10.1023/A:1012809914301.

2. Beckmann, N., Kriegel, H., Schneider, R., et al. (1990). The R*-Tree: an efficient and robust access method for points and rectangles. In SIGMOD conference (pp. 322–331). ACM Press. https://doi.org/10.1145/93605.98741

3. Bentley, J. L. (1975). Multidimensional binary search trees used for associative searching. Communications of the ACM, 18(9), 509–517. https://doi.org/10.1145/361002.361007.

4. Chen, G., Zhao, J., Gao, Y., et al. (2017). Time-aware Boolean spatial keyword queries. IEEE Transactions on Knowledge and Data Engineering, 29(11), 2601–2614. https://doi.org/10.1109/TKDE.2017.2742956.

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

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