Implementation of a Community Data Processing System Based on Data Mining

With the development of social information technology, intelligent community as a new way of life is changing people's lives step by step. The community as a unit of residence in China has developed quite maturely, but the community services are not perfect, and the management is relatively mechanized. Therefore, improving work efficiency and enriching and perfecting community service is an increasingly important issue. Data mining is to extract valuable information by analyzing the internal connections, rules, and patterns of these data so as to provide more favorable decision support for community managers and provide users with more humane and modern community intelligence services. This research focuses on the implementation of community data processing systems based on data mining. Firstly, data preprocessing analysis is carried out, the realization of data storage and cache is studied, the process and characteristics of cluster analysis are studied in detail, and the simulation results of a community data processing system based on data mining are summarized. This study uses data mining technology to dig out the daily consumption data of users in the community mall, cluster the data, and analyze the consumption situation and consumption types of different types of users. In this study, data mining technology is used to mine the fault repair data of the community, and classification prediction technology is used to classify and predict different types of faults so as to help managers troubleshoot problems existing in the community environment.