Method of Demand Forecasting of Urban Landscaping Information Management Based on Text Mining

Assisting daily landscaping management with the means of informationization can greatly improve the efficiency and precision of management. Accurate, full and frontier user demand analysis is the basis for the establishment of an urban landscaping information management system, and platform top-level architecture, functional composition, and module design. However, due to the specialty deviation in information construction and landscaping industry management, the communication barriers between the informatization demand analysis and industry forecasting are high. According to the characteristics of big data, this paper puts forward a set of scientific methods for demand analysis and forecast of urban landscaping information management with the text mining method, which fully combines the user application evaluation, network news and meeting minutes and other text big data. It analyzes the characteristics of high frequency words obtained from the three types of text mining and, along with the actual investigation of the urban landscaping information industry in the early stage, to reach the characteristics of demand prominent in the front-end management of hierarchical transformation, office automation, Internet of Things awareness in the current management goal of Chinese landscaping, putting forward the direction of construction to promote the information work of landscaping industry.