Abstract
In this paper, a persona and users’ segmentation model are established by analyzing the power users’ data. In order to further complete the historical database, the paper adopts the method of questionnaire to collect information. Then according to the characteristics of power users, the index system is established, and the index is selected. Different construction methods are adopted for different models. Here, the K-means algorithm is used to cluster the second level indicators in the users’ behavior attribute, and the users’ label is extracted according to the clustering results. Finally, power users’ persona is implemented. It can be proved that the model is effective in dealing with massive data, and provides reliable data support for decision making.
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This work is supported by the National Natural Science Foundation of China (61403073).
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Ren, X., Hui, G., Luo, Y., Wang, Y., Yang, D., Qi, G. (2017). Power Users Behavior Analysis and Application Based on Large Data. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10638. Springer, Cham. https://doi.org/10.1007/978-3-319-70139-4_11
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DOI: https://doi.org/10.1007/978-3-319-70139-4_11
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