摘要
[目的 /意义]Folksonomy知识组织模式中的标签呈现离散混沌的社群知识标注状态,对知识群落进行构建和分析能够揭示出知识之间潜在的关联和核心知识。[方法 /过程]采用复杂网络分析的理论和方法识别和构建社群知识网络中的知识群落,并对群落结构以及群落核心知识的伴生关联进行分析。[结果/结论]从知识网络的视角提取并分析Folksonomy模式中网状结构下知识群落嵌套的层级结构,并对知识群落中的核心知识以及知识的伴生性进行揭示。
[ Purpose/significance ] The community knowledge tagging status of user tags are discrete and chaos in the folksonomy knowledge organization mode. Therefore, building and analyzing knowledge communities can reveal the po- tential association between knowledge and core knowledge. [ Method/process ] The knowledge communities were built and analyzed in the community knowledge network with complex network theories and methods, and the structure of knowl- edge communities and accompanying association of core knowledge were analyzed. [ Result/conclusion] The nested hier- archical structure of knowledge communities is extracted and analyzed in the folksonomy mode fromthe knowledge network perspective. The core knowledge and accompanying attributes of knowledge are revealed in knowledge communities.
出处
《图书情报工作》
CSSCI
北大核心
2015年第22期124-129,共6页
Library and Information Service
基金
国家自然科学基金项目"基于网络结构演化的Folksonomy模式中社群知识组织与知识涌现研究"(项目编号:71473035)
教育部人文社会科学研究规划基金项目"基于后结构主义网络分析的Folksonomy模式中社群知识非线性自组织研究"(项目编号:14YJA870010)研究成果之一
