摘要
随着数字阅读平台的不断推广,参与知识付费的用户比例也大幅增加。文章采用问卷调查法收集用户相关信息,选取用户的部分行为变量进行研究,使用SPSS 19.0软件将这些变量进行描述统计和提取公因子,再利用K-Means算法进行聚类,从而得到4种不同类型的用户画像。通过分析不同用户类型的特点,有助于数字阅读平台的进一步优化,为不同用户个性化服务提供了参考与建议。
With the continuous promotion of digital reading platforms,the proportion of users participating in knowledge payment has also significantly increased.The article uses a questionnaire survey method to collect user related information,selects some behavioral variables of users for research,uses SPSS 19.0 software to describe and statistically analyze these variables and extract common factors,and then uses K-Means algorithm for clustering to obtain four different types of user images.By analyzing the characteristics of different user types,it is helpful for further optimization of digital reading platforms and provides reference and suggestions for personalized services for different users.
作者
黄楚楚
贾文丽
HUANG Chuchu;JIA Wenli(School of Computer Science and Engineering,Shandong University of Science and Technology,Qingdao 266590,China;Archives,Shandong University of Science and Technology,Qingdao 266590,China)
出处
《江苏科技信息》
2025年第5期83-87,共5页
Jiangsu Science and Technology Information
关键词
数字阅读平台
知识付费
用户画像
聚类
digital reading platform
knowledge payment
user profile
clustering
