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- W4352982020 abstract "The purpose of studying the consumer behavior of enterprise customers is to maintain a long-term exchange relationship with customers, and to facilitate the formulation of corresponding marketing strategies. This paper focuses on the research of customer's consumption behavior, compares the advantages and disadvantages of current related algorithms on customer's consumption behavior, and finally chooses fuzzy clustering algorithm for customer segmentation research, uses association rules based on changes of customer's consumption behavior pattern to build a prediction model, and deeply understands these algorithms, and puts forward corresponding improvements aiming at the shortcomings of the algorithms. Finally, it is verified by experiments that the average relative error and root mean square error of the prediction system before and after the improvement are low, but it can be clearly seen that the improved prediction system has smaller error than the traditional system, indicating that the improved prediction system has higher prediction accuracy. Clustering algorithm in DM(data mining) technology is used to segment customers. The selection of methods and attributes is the decisive factor for the effectiveness of clustering algorithm. It can be said that these two aspects are crucial factors for all DM methods." @default.
- W4352982020 created "2023-03-23" @default.
- W4352982020 creator A5057739867 @default.
- W4352982020 date "2022-11-01" @default.
- W4352982020 modified "2023-09-30" @default.
- W4352982020 title "Analysis of Data Mining Mode of Customer Consumption Behavior Based on Fuzzy Clustering Algorithm" @default.
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- W4352982020 doi "https://doi.org/10.1109/ispcem57418.2022.00038" @default.
- W4352982020 hasPublicationYear "2022" @default.
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