面向用户认知需求的图书馆用户画像研究

Research on Library User Portraits for User Cognitive Needs

借鉴用户认知需求的研究现状以及用户画像在图书馆的应用实践,提出面向用户认知需求的图书馆用户画像系统模型,在标签体系中选取用户基本属性数据、动态行为属性数据、互动属性数据、偏好属性数据,借助文本处理、深度学习等技术以及社区发现、标签传播等监督技术对数据分别处理和预测,并提出基于用户认知的需求预测、个性化体现、社区发现、决策调整4大分析应用,对于构建、完善用户画像认知体系有较大的促进作用。

Based on the research status of user's cognitive needs and the application practice of user portraits in the library,this paper proposes a library user portrait system model for user cognitive needs,and selects user basic attributive data,dynamic behavior attributive data and interactive attributive data in the label system,reference attributive data,using text processing,deep learning and other techniques,as well as community discovery,label propagation and other monitoring techniques to separately process and predict data,It also proposes four major analytical applications based on user cognition,demand forecasting,personalized embodiment,community discovery,and decision-making adjustment,which will greatly promote the construction of a complete user profile cognition system.