A MapReduce approach for spatial co-location pattern mining via ordered-clique-growth-Reference-Cited by-同舟云学术

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A MapReduce approach for spatial co-location pattern mining via ordered-clique-growth

Published:2019-12-02 Issue:2 Volume:38 Page:531-560
ISSN:0926-8782
Container-title:Distributed and Parallel Databases
language:en
Short-container-title:Distrib Parallel Databases

Author:

Yang Peizhong,Wang Lizhen,Wang Xiaoxuan

Funder

The National Natural Science Foundation of China

The Project of Innovative Research Team of Yunnan Province

Publisher

Springer Science and Business Media LLC

Subject

Information Systems and Management,Hardware and Architecture,Information Systems,Software

Link

http://link.springer.com/content/pdf/10.1007/s10619-019-07278-7.pdf

Reference45 articles.

1. Shekhar, S., Huang, Y.: Discovering spatial co-location patterns: a summary of results. In: 7th International Symposium on Advances in Spatial and Temporal Databases (SSTD), pp. 236–256 (2001)

2. Yoo, J.S., Shekhar, S.: A joinless approach for mining spatial colocation patterns. IEEE Trans. Knowl. Data Eng. 18(10), 1323–1337 (2006)

3. Huang, Y., Shekhar, S., Xiong, H.: Discovering colocation patterns from spatial data Sets: a general approach. IEEE Trans. Knowl. Data Eng. 16(12), 1472–1485 (2004)

4. Xiong, H., Shekhar, S., Huang, Y., Kumar, V., Ma, X., Yoo, J.S.: A framework for discovering co-location patterns in data sets with extended spatial objects. In: SIAM International Conference on Data Mining, pp. 1–13 (2004)

5. Mohammad, A., Farhad, S., Robert, W.: A generic regional spatio-temporal co-occurrence pattern mining model: a case study for air pollution. J. Geogr. Syst. 17(3), 249–274 (2015)

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