The Application of the Analytic Hierarchy Process and a New Correlation Algorithm to Urban Construction and Supervision Using Multi-Source Government Data in Tianjin

As the era of big data approaches, big data has attracted increasing amounts of attention from researchers. Various types of studies have been conducted and these studies have focused particularly on the management, organization, and correlation of data and calculations using data. Most studies involving big data address applications in scientific, commercial, and ecological fields. However, the application of big data to government management is also needed. This paper examines the application of multi-source government data to urban construction and supervision in Tianjin, China. The analytic hierarchy process and a new approach called the correlation degree algorithm are introduced to calculate the degree of correlation between different approval items in one construction project and between different construction projects. The results show that more than 75% of the construction projects and their approval items are highly correlated. The results of this study suggest that most of the examined construction projects are well supervised, have relatively high probabilities of satisfying the relevant legal requirements, and observe their initial planning schemes.