Research on User Profile and User Behavior of Integrating Big Data Platforms

Yaoxuan Wang
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Abstract

This paper discusses the construction and analysis method of user behavioral portrait by the data provided by the electric power platform in the big data environment. Firstly, it introduces the construction and analysis of user profiles based on big data platforms, which covers the construction of user basic attribute profiles, user behavioral characteristics profiles, user product characteristics profiles and user interaction characteristics profiles from different dimensions. Secondly, for the electric power sector, the article discusses the analysis of big data provided by electric power platforms to better understand user behavior and trends in energy consumption. The article proposes a method for constructing a behavioral portrait of power users based on big data analysis, including the construction and management of a user label library and the process of constructing a behavioral portrait of power users based on the improved K-mean algorithm. Finally, the effectiveness and accuracy of the method of this paper are verified by experimental analysis. Overall, this paper provides some guidance and reference for the analysis of user behavior in the field of electric power by exploring the method of user behavior portrait construction with the data provided by the electric power platform in the big data environment.
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大数据平台整合的用户画像与用户行为研究
本文探讨了大数据环境下电力平台提供的数据对用户行为画像的构建与分析方法。首先,文章介绍了基于大数据平台的用户画像构建与分析方法,包括从不同维度构建用户基本属性画像、用户行为特征画像、用户产品特征画像和用户交互特征画像。其次,针对电力行业,文章探讨了如何分析电力平台提供的大数据,以更好地了解用户行为和能源消耗趋势。文章提出了一种基于大数据分析的电力用户行为画像构建方法,包括用户标签库的构建和管理,以及基于改进的 K-mean 算法构建电力用户行为画像的过程。最后,通过实验分析验证了本文方法的有效性和准确性。总之,本文利用大数据环境下电力平台提供的数据,探索用户行为画像构建方法,为电力领域用户行为分析提供了一定的指导和参考。
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