RT Journal Article
A1 Shubing Shan
AD China Intelligent Urbanization Co-Creation Center, No. 1239, Siping Road, Shanghai, People's Republic of China
AD School of Software Engineering, Tongji University, No. 4800, Caoan Road, Shanghai, People's Republic of China
A1 Buyang Cao
AD China Intelligent Urbanization Co-Creation Center, No. 1239, Siping Road, Shanghai, People's Republic of China
AD School of Software Engineering, Tongji University, No. 4800, Caoan Road, Shanghai, People's Republic of China

PB iet
T1 Follow a guide to solve urban problems: the creation and application of urban knowledge graph
JN IET Software
VO 11
IS 3
SP 126
OP 134
AB It is a hot research topic today to find out the potential knowledge from the scattered urban data and take advantage of the relationship between the knowledge to solve the challenges of urban governance and smart city construction. The urban knowledge graph is an effective way to establish the relationship between the knowledge and address the urban issues. This study proposes the methodology to create an urban knowledge graph and its framework. It elaborates the approaches of urban knowledge acquisition, reasoning and expression. Furthermore, a hybrid reasoning algorithm known as EG is given based on expectation-maximisation algorithm and Gibbs algorithm, which has the complementary advantages of the both methods. Through a study case, this study illustrates constructing and working process of an urban knowledge graph. The case shows that the urban knowledge graph has a good application prospect.
K1 hybrid reasoning algorithm
K1 Gibbs algorithm
K1 urban knowledge graph
K1 expectation-maximisation algorithm
K1 EG
K1 urban knowledge acquisition
K1 urban problems
DO https://doi.org/10.1049/iet-sen.2016.0189
UL https://digital-library.theiet.org/;jsessionid=41k8s0tirmlai.x-iet-live-01content/journals/10.1049/iet-sen.2016.0189
LA English
SN 1751-8806
YR 2017
OL EN