Academy & Industry Research Collaboration Center
Data mining is an effective method of discovering useful information in a large amount of data. The capability of understanding the user's consumption is vital for a company. Discovering the significant customers allows the company to focus on the most valuable customers. This paper uses micro-blog users' check-in data and shop information for analysis and cluster method of data mining. The authors analyze user's spending ability quantitatively based on user's check-in actions. Compared with other clustering method, they choose DBSCAN clustering method of data mining to analyze the shop information and position.