摘要
[目的/意义]构建与分析移动图书馆UGC用户画像模型,挖掘用户潜在信息需求,促进移动图书馆UGC实现精准化推荐服务。[方法/过程]通过Python爬取喜马拉雅APP《三体》的部分评论数据并进行聚类分析;利用RFM模型选取典型用户;采用TF-IDF算法生成标签,利用词云可视化工具生成典型用户的完整画像。[结果/结论]详细阐述移动图书馆UGC用户画像的构建流程,并通过实例分析构建喜马拉雅平台《三体》部分典型用户的完整画像,提出移动图书馆应结合数据驱动的用户画像提供精准化的推荐服务、个性化的知识搜索、智慧化的预测服务、智能化的隐私保护,以促进移动图书馆UGC精准服务的实现。
[Purpose/significance] Constructing and analyzing mobile library UGC user profile models can dig out users’ potential information needs and promote mobile library UGC to achieve precise recommendation services.[Method/process] Crawling part of the comment data of the Himalaya APP “Three Body” through Python and performing cluster analysis;using the RFM model to select typical users;using the TF-IDF algorithm to generate tags, and using word cloud visualization tools to generate complete portraits of typical users.[Result/conclusion] Explain in detail the construction process of mobile library UGC user portraits, and construct complete portraits of some typical users of the Himalaya platform “Three Body” through case analysis, and propose that mobile libraries should combine data-driven user portraits to provide accurate recommendation services and personalization knowledge search, intelligent forecasting services, and intelligent privacy protection to promote the realization of mobile library UGC precise services.
出处
《情报理论与实践》
CSSCI
北大核心
2022年第1期30-37,共8页
Information Studies:Theory & Application
基金
国家自然科学基金青年项目“基于网络生态的知识付费行为及安全治理模式研究”(项目编号:71804057)
吉林省科技厅科技战略与规划研究项目“吉林省农民知识付费行为及安全治理模式研究”(项目编号:20200101059FG)
吉林大学哲学社会科学研究种子基金项目“基于多维内容消费矩阵的知识付费模式及生态优化研究”(项目编号:2019ZZ022)的成果。
