Application Of Data Mining Technology In Property Management

In the process of growing social information today, people are concerned about the residential area is no longer confined to living room, the surrounding environment and so on, but to focus more attention on communication with the outside world, information services, safety precautions, the property management, etc., precisely in order to adapt to the needs of society, residential quarters intelligent management systems have come into being. Residential District based on the current status of domestic intelligence and trends, development suited to China's national conditions and intelligent management of the district system is to develop a strong guarantee for Intelligent Community. This intelligent management system should take full account of Intelligent Community of the status quo and development trend of management flexibility to meet the residential, security and economy. In property management, property management system will face a lot of from the user's data and information, these data are numerous, are not complete, there is noise, and vague, random, but at the same time is very useful. Data mining technology can effectively analyze these data, sorting, and thus to the data the user to provide effective and timely information.This paper briefly discusses the overall framework of the property management system, focusing on residential property management in intelligent data mining in the cluster analysis method was applied to the property management in the forecasting process a malicious user arrears. The theoretical basis of the study, further data mining is given in the property management industry owe a malicious user prediction analysis of the application example. Application of data mining tools to analyze property management fee is causing malicious default risk factors, to help property management companies to find the main factors causing this problem, and even found that some analysts may have never thought about or tried other factors.