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Article

Uncorrelated Geo-Text Inhibition Method Based on Voronoi K-Order and Spatial Correlations in Web Maps

by 1,2,3, 1,2,3,*, 1,2,3, 1,2,3 and 1,2,3
1
School of Geography, Nanjing Normal University, Nanjing 210023, China
2
Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, China
3
Jiangsu Center for Collaborative Innovation in Geographical Information, Resource Development and Application, Nanjing 210023, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(6), 381; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9060381
Received: 29 April 2020 / Revised: 27 May 2020 / Accepted: 5 June 2020 / Published: 9 June 2020
Unstructured geo-text annotations volunteered by users of web map services enrich the basic geographic data. However, irrelevant geo-texts can be added to the web map, and these geo-texts reduce utility to users. Therefore, this study proposes a method to detect uncorrelated geo-text annotations based on Voronoi k-order neighborhood partition and auto-correlation statistical models. On the basis of the geo-text classification and semantic vector transformation, a quantitative description method for spatial autocorrelation was established by the Voronoi weighting method of inverse vicinity distance. The Voronoi k-order neighborhood self-growth strategy was used to detect the minimum convergence neighborhood for spatial autocorrelation. The Pearson method was used to calculate the correlation degree of the geo-text in the convergence region and then deduce the type of geo-text to be filtered. Experimental results showed that for given geo-text types in the study region, the proposed method effectively calculated the correlation between new geo-texts and the convergence region, providing an effective suggestion for preventing uncorrelated geo-text from uploading to the web map environment. View Full-Text
Keywords: geo-text; spatial autocorrelation; Voronoi k-order; volunteered geographic information; semantic analysis; text auto-classification geo-text; spatial autocorrelation; Voronoi k-order; volunteered geographic information; semantic analysis; text auto-classification
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MDPI and ACS Style

He, Y.; Sheng, Y.; Jing, Y.; Yin, Y.; Hasnain, A. Uncorrelated Geo-Text Inhibition Method Based on Voronoi K-Order and Spatial Correlations in Web Maps. ISPRS Int. J. Geo-Inf. 2020, 9, 381. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9060381

AMA Style

He Y, Sheng Y, Jing Y, Yin Y, Hasnain A. Uncorrelated Geo-Text Inhibition Method Based on Voronoi K-Order and Spatial Correlations in Web Maps. ISPRS International Journal of Geo-Information. 2020; 9(6):381. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9060381

Chicago/Turabian Style

He, Yufeng, Yehua Sheng, Yunqing Jing, Yue Yin, and Ahmad Hasnain. 2020. "Uncorrelated Geo-Text Inhibition Method Based on Voronoi K-Order and Spatial Correlations in Web Maps" ISPRS International Journal of Geo-Information 9, no. 6: 381. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9060381

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