摘要
【目的】通过引入社会网络分析理论,解决知识推送服务中隐性知识推送不足的问题。【应用背景】在数字图书馆数据库的访问日志的环境下,选取24小时内登录用户的知识偏好为实验数据开展研究。【方法】通过引入"n-团子群"与"点度中心性"概念分析目标用户群,将相似用户的隐性知识需求显性化共现并对相关知识实体加以推送。【结果】发现推送隐性知识的广度与精准度直接受n-团子群的参数n值影响,将其值设置为2能够保证推送的隐性知识更具颗粒性。【结论】解决知识推送服务中数据极端稀缺、用户隐含的知识需求获取力度差的问题,促进隐性知识交流。
[Objective] Introduce the theory of social network analysis to solve the problem in implicit knowledge push service. [Context] The research is carried out by selecting the knowledge preference of logined users within 24 hours based on the digital library environment. [Methods] ＂N-cliques ＂ and ＂centrality degree＂ are introduced to analyze the target users, Make the similar users＇ implicit knowledge requirement explicit and push knowledge to target users. [Results] The breadth and accuracy of implicit knowledge pushing performance is directly affected by parameter of ＂n＂, and the implicit knowledge pushed is of more granularity when the threshold is set to ＂2＂ . [Conclusions] Our research solved the issue of extreme scarcity of pushing data and poor performance of users＇ implicit knowledge acquirement, promoting the share of implicit knowledge.
出处
《现代图书情报技术》
CSSCI
北大核心
2014年第2期48-54,共7页
New Technology of Library and Information Service
基金
国家自然科学基金项目"语义网络环境下数字图书馆资源多维度聚合与可视化展示研究"(项目编号:71273111)
国家社会科学基金重大项目"基于语义的馆藏资源深度聚合与可视化研究"(项目编号:11&ZD152)
吉林大学985工程项目的研究成果之一
关键词
社会网络分析
知识推送
n-团子群
隐性知识共现
Social network analysis Knowledge push service N-cliques Implicit knowledge co-occurrence
