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Open AccessArticle

Concept Lattice Method for Spatial Association Discovery in the Urban Service Industry

1
College of Mathematics and Information Science, Guangxi University, Nanning 530004, China
2
School of Information and Engineering, Sichuan Tourism University, Chengdu 610100, China
3
State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(3), 155; https://doi.org/10.3390/ijgi9030155
Received: 12 February 2020 / Accepted: 8 March 2020 / Published: 9 March 2020
A relative lag in research methods, technical means and research paradigms has restricted the rapid development of geography and urban computing. Hence, there is a certain gap between urban data and industry applications. In this paper, a spatial association discovery framework for the urban service industry based on a concept lattice is proposed. First, location data are used to form the formal context expressed by 0 and 1. Frequent closed itemsets and a concept lattice are computed on the basis of the formal context of the urban service industry. Frequent closed itemsets can filter out redundant information in frequent itemsets, uniquely determine the complete set of all frequent itemsets, and be orders of magnitude smaller than the latter. Second, spatial frequent closed itemsets and association rules discovery algorithms are designed and built based on the formal context. The inputs of the frequent closed itemsets discovery algorithms include the given formal context and frequent threshold value, while the outputs are all frequent closed itemsets and the partial order relationship between them. Newly added attributes create new concepts to guarantee the uniqueness of the new spatial association concept. The inputs of spatial association rules discovery algorithms include frequent closed itemsets and confidence threshold values, and a rule is confident when and only if its confidence degree is not less than the confidence threshold value. Third, the spatial association of the urban service industry in Nanning, China is taken as a case to verify the method. The results are basically consistent with the spatial distribution of the urban service industry in Nanning City. This study enriches the theories and methods of geography as well as urban computing, and these findings can provide guidance for location-based service planning and management of urban services. View Full-Text
Keywords: concept lattice; frequent closed itemset; spatial association; urban service industry concept lattice; frequent closed itemset; spatial association; urban service industry
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MDPI and ACS Style

Liao, W.; Zhang, Z.; Jiang, W. Concept Lattice Method for Spatial Association Discovery in the Urban Service Industry. ISPRS Int. J. Geo-Inf. 2020, 9, 155. https://doi.org/10.3390/ijgi9030155

AMA Style

Liao W, Zhang Z, Jiang W. Concept Lattice Method for Spatial Association Discovery in the Urban Service Industry. ISPRS International Journal of Geo-Information. 2020; 9(3):155. https://doi.org/10.3390/ijgi9030155

Chicago/Turabian Style

Liao, Weihua; Zhang, Zhiheng; Jiang, Weiguo. 2020. "Concept Lattice Method for Spatial Association Discovery in the Urban Service Industry" ISPRS Int. J. Geo-Inf. 9, no. 3: 155. https://doi.org/10.3390/ijgi9030155

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