情报科学 ›› 2022, Vol. 39 ›› Issue (1): 88-93.

• 理论研究 • 上一篇    下一篇

基于用户动态画像的学术新媒体信息精准推荐模型研究 

  

  • 出版日期:2022-01-01 发布日期:2022-01-12

  • Online:2022-01-01 Published:2022-01-12

摘要: 【目的/意义】构建基于用户动态画像的学术新媒体信息精准推荐模型是满足学术新媒体用户对学术信息
资源精准化、个性化与专业化的要求,同时也是提高学术信息流转效率以及价值增值的有效途径。【方法
/过程】在
探究学术新媒体信息流转模型的基础上,进一步分析学术新媒体用户需求与分层画像,重构学术新媒体用户画像
步骤,构建基于用户动态画像的学术新媒体信息精准推荐模型。【结果
/结论】基于用户动态画像的学术新媒体信息
精准推荐模型能够实现学术信息资源与用户的精准对接,提升用户忠诚度,更好地服务科研工作者的学术活动。
【创新
/局限】从理论框架角度分析与构建学术新媒体信息推荐模型,后续将重点研究模型的技术实现与实践应用。

Abstract: Purpose/significanceThe construction of accurate recommendation model of academic information based on user dynamic portrait is to meet the requirements of academic new media users for the precision,personalization and specialization of academic new media information resources,and it is also an effective way to improve the efficiency of academic information flow and value-added.Method/processThis paper explores the information flow model of academic new media ,and further analyzes the user demand and hi⁃erarchical portrait of academic new media.On this basis,it reconstructs the steps of user portrait of academic new media,and constructs the recommendation model of academic new media information resources based on user dynamic profile. Result/conclusionThe accu⁃
rate recommendation model of academic new media information based on user dynamic portrait can realize the accurate docking be⁃tween academic information resources and users,enhance user loyalty ,better serve the academic activities of scientific researchers
. In⁃novation/limitationThis paper analyzes and constructs the academic new media information recommendation model from the perspec⁃tive of theoretical framework,and will focus on the technical implementation and practical application of the model.