Affiliations: [a]
College of International Education, Guangxi University of Finance and Economics, Nanning, China
| [b]
Economic and Trade College, Guangxi University of Finance and Economics, Nanning, China
Correspondence:
[*]
Corresponding author. Shuting Wen, College of International Education, Guangxi University of Finance and Economics, Nanning 530000, China. E-mail: [email protected].
Abstract: Culture and tourism development through public services rely on accumulated big data and overall country/ province development. Accumulated data relies on various cultures, people, places, etc. attributes for which a heterogeneous and multi-faced analysis is required. This article introduces a Development-focused Data Handling Process (D-DHP) for providing insights through culture and tourism accumulated information. The proposed process relies on heterogeneous data attributes for identifying economic and society-based development stagnancies. The data analysis is performed for identifying missing sequences and invariable information that shows development stagnancies. The stagnancy rates between successive quarters (per annum) are accounted for identifying development drops. If such drops are identified, the accumulated data outputs are analyzed through classification learning. In this classification, the development and drop-associated data are split for an independent analysis. This analysis helps to replace the mode of development focusing on tourism or culture or both based on dependability. The classification process is updated based on the replaced information for further improvements across various accumulated data inputs. Therefore, the proposed process is viable in identifying development-focused information from the accumulated data.
Keywords: Big data, classification learning, culture and tourism, public services
