Design And Implementation Of Real Estate Enterprise Sales System Based On Hybrid GBDT

As one of the basic industries in China,the real estate industry contributes a lot of income to the national GDP every year,which plays an important role in stimulating the economy.Since the housing reform in the 1990 s,the real estate industry has accumulated a large number of sales data,customer data and construction data,but the real estate industry is still in the stage of extensive collection and utilization of data.Therefore,for the accumulated large amount of data,the use is not sufficient.Therefore,it is particularly important to develop a set of real estate enterprise sales management system based on data mining technology,using modern data mining technology to improve the efficiency of enterprise sales management.This system uses three-tier architecture to divide it into three parts: presentation layer,logic layer and data access layer.Using MVC design mode: M(model)model,V(view)view and C(controller)controller,the presentation layer in the three-tier architecture is further divided into two parts: view and controller,effectively reducing system coupling and improving the reusability of server-side code.Using j Query,div + CSS and other plug-ins to beautify the interface,using bootstrap framework to make a responsive layout of the system interface,so that the system can easily support the access of various computers,mobile phones,tablets and other browsing devices,so as to facilitate the system transplantation and reuse;using Web Service Interface Technology to realize the docking of all kinds of systems.This paper makes full use of the historical records and user records of the real estate industry,and designs a prediction model of customer screening and house source matching based on data mining,which can improve the accuracy of screening and prediction,improve the sales efficiency of real estate enterprises,and play a very good auxiliary role in real estate decision-making and sales personnel.