A Case Study on Spatio-Temporal Data Mining of Urban Social Management Events Based on Ontology Semantic Analysis

Shaohua Wang, Xianxiong Liu, Haiyin Wang and Qingwu Hu
Additional contact information
Shaohua Wang: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
Xianxiong Liu: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
Haiyin Wang: Institute of Qingdao Geotechnical Investigation and Surveying, Qingdao 266071, China
Qingwu Hu: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China

Sustainability, 2018, vol. 10, issue 6, 1-24

Abstract: The massive urban social management data with geographical coordinates from the inspectors, volunteers, and citizens of the city are a new source of spatio-temporal data, which can be used for the data mining of city management and the evolution of hot events to improve urban comprehensive governance. This paper proposes spatio-temporal data mining of urban social management events ( USMEs ) based on ontology semantic approach. First, an ontology model for USMEs is presented to accurately extract effective social management events from non-structured UMSEs . Second, an explorer spatial data analysis method based on “event-event” and “event-place” from spatial and time aspects is presented to mine the information from UMSEs for the urban social comprehensive governance. The data mining results are visualized as a thermal chart and a scatter diagram for the optimization of the management resources configuration, which can improve the efficiency of municipal service management and municipal departments for decision-making. Finally, the USMEs of Qingdao City in August 2016 are taken as a case study with the proposed approach. The proposed method can effectively mine the management of social hot events and their spatial distribution patterns, which can guide city governance and enhance the city’s comprehensive management level.

Keywords: city management; spatial-temporal event; ontology; semantic; data mining (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/10/6/2084/pdf (application/pdf)
https://www.mdpi.com/2071-1050/10/6/2084/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:10:y:2018:i:6:p:2084-:d:153317

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().