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

Yaoxuan Wang
{"title":"Research on User Profile and User Behavior of Integrating Big Data Platforms","authors":"Yaoxuan Wang","doi":"10.62051/3a6dex21","DOIUrl":null,"url":null,"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.","PeriodicalId":515906,"journal":{"name":"Transactions on Economics, Business and Management Research","volume":"36 50","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transactions on Economics, Business and Management Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.62051/3a6dex21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

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.
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信