摘要
用户画像作为大数据分析背景下个性化推荐服务的设计工具,为高校图书馆领域个性化阅读资源推荐服务提供解决思路。本研究在分析目前个性化推荐和用户画像研究的基础上,引入用户画像技术,从数据基础层、数据处理层、画像构建层、画像服务层设计探讨用户画像的构建流程,重点在用户画像构建和画像服务层面进行阐述,同时从用户基本属性、阅读状态、学习风格、阅读偏好四个维度构建用户多维画像模型,并提出基于冷启动和用户阅读学习过程画像的个性化推荐服务策略,以期为后疫情教育环境下高校图书馆开展个性化资源推荐服务和满足用户多维度阅读学习需求提供参考。
As a design tool for personalized recommendation services in the context of the big data analysis,user portrait provides solutions for personalized reading resource recommendation services in the field of university libraries.Based on the analysis of current personalized recommendation and user portrait research,this research introduces user portrait technology to discuss the construction process of user portrait from the design of the data foundation layer,data processing layer,portrait construction layer and portrait service layer.Then explanation focused on the level of portrait construction and portrait service.At the same time,it constructs a users’multi-dimensional portrait model from the four dimensions of users’basic attributes,reading status,learning style and reading preference.Finally,personalized recommendation service strategy based on the cold start and user portrait during the user’s reading and learning process are proposed,in order to provide reference for university libraries to develop personalized resource recommendation services and meet users’multi-dimensional reading and learning needs in the post-epidemic education environment.
出处
《新世纪图书馆》
CSSCI
2021年第4期68-75,共8页
New Century Library
基金
陕西省教育科学“十三五”规划2020年度课题“教育大数据下基于学习者画像的个性化推荐服务研究”(项目编号:SGH20Q265)
2020年安康学院青年基金项目“教育大数据下用户画像的构建及应用研究”(项目编号:2020AYQN01)阶段性研究成果之一。
关键词
用户画像
个性化资源推荐
阅读偏好
冷启动
User portrait
Personalized resources recommendation
Interest preference
Cold start
