数据融合视域下虚拟知识社区知识推荐模型构建
Construction of Knowledge Recommendation Model in Virtual Knowledge Community from the Perspective of Data Fusion
郭小光1
作者信息
- 1. 北京科技大学天津学院图书馆,天津,301830
- 折叠
摘要
文章采用扎根理论方法分析虚拟知识社区用户需求,构建虚拟知识社区用户知识需求框架,在此基础上提出虚拟知识社区数据融合方法,进而构建基于数据融合的虚拟知识社区知识推荐模型,并从用户画像、情感感知、社交网络3个角度提出虚拟知识社区知识推荐优化路径.
Abstract
The article adopts the grounded theory method to analyze the user needs of virtual knowledge communities,and proposes a data fusion method for virtual knowledge communities,build a virtual knowledge community user knowledge needs framework.Based on this,a personalized knowledge recommendation model for virtual knowledge communities is constructed,and optimization paths for virtual knowledge community knowledge recommendation is proposed from three perspectives:user profile,emotional perception,and social network.
关键词
虚拟知识社区/知识推荐/推荐模型/数据融合/开放科学Key words
Virtual knowledge community/Knowledge recommendation/Recommended model/Data fusion/Open science引用本文复制引用
基金项目
天津市哲学社会科学规划基金青年项目(TJTQQN20-001)
出版年
2024
NETL
NSTL
万方数据