基于知识网络的标签层级演化研究
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摘要
[目的/意义]基于知识网络的核心-边缘结构揭示Folksonomy知识组织模式中标签层级演化的模式与规律,对洞悉开放网络环境下知识组织的层级结构具有重要意义。[方法/过程]以网络思维为指导,基于标签之间的同现关系构建领域知识网络。依据核心-边缘结构分析方法,遵循时间序列对标签层级的演化情况,从描述统计、显著性分析、层级升降演化等方面进行跟踪研究。[结果/结论]标签的核心/边缘层级结构随着领域知识的发展演化变迁,逐渐收敛趋于稳定。标签层级的晋升与淡化主要受知识关联驱动,核心层标签之间的关联关系占有更高的权重。标签层级演化规律的揭示,有助于把握Folksonomy模式中知识组织的结构特征,对于揭示开放网络环境下知识关联及其结构关系具有积极的促进作用。
[Purpose/significance]Core-periphery structure of knowledge networks can reveal the laws and models of tags hierarchy evolution. The detection has important significance for insight into hierarchical structure of knowledge organization in the open network environment. [Method/process]Under the guidance of network thinking,the domain knowledge networks are constructed based on the co-occurrence relationships between tags. According to the core-periphery structure analysis method,the evolution of the tags hierarchyon time series is tracked from the description of statistics,significant analysis,and rising/falling of tags hierarchy. [Result/conclusion] The results show that the tags hierarchy of core/peripherystructure changes with the development of domain knowledge,and gradually approaches stabilize. The rising and falling of tags hierarchy are mainly driven by knowledge cross-correlation and the relationships between core layer tags occupy a higher weight. These rules of hierarchy evolution help to grasp the structural features of the knowledge organizationin the folksonomy model,and help to promote positive role for revealing the knowledge cross-correlation and structural relations in the open network environment.
[Purpose/significance]Core-periphery structure of knowledge networks can reveal the laws and models of tags hierarchy evolution. The detection has important significance for insight into hierarchical structure of knowledge organization in the open network environment. [Method/process]Under the guidance of network thinking,the domain knowledge networks are constructed based on the co-occurrence relationships between tags. According to the core-periphery structure analysis method,the evolution of the tags hierarchyon time series is tracked from the description of statistics,significant analysis,and rising/falling of tags hierarchy. [Result/conclusion] The results show that the tags hierarchy of core/peripherystructure changes with the development of domain knowledge,and gradually approaches stabilize. The rising and falling of tags hierarchy are mainly driven by knowledge cross-correlation and the relationships between core layer tags occupy a higher weight. These rules of hierarchy evolution help to grasp the structural features of the knowledge organizationin the folksonomy model,and help to promote positive role for revealing the knowledge cross-correlation and structural relations in the open network environment.
引文
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[24]GLEICK J.信息简史[M].高博,译.北京:人民邮电出版社,2013:409-421.
[2]PETERS I,WELLER K.Tag gardening for folksonomy enrichment and maintenance[J].Webology,2008,5(3):1-18.
[3]LANIADO D,EYNARD D,COLOMBETTI.Using Word Net to turn a folksonomy into a hierarchy of concepts[C]//Semantic web application and perspectives-fourth Italian semantic web workshop.Bari:CEUR,2007:192-201.
[4]SHEPITSEN A,GEMMELL J,MOBASHER B,et al.Personalized recommendation in social tagging systems using hierarchical clustering[C]//Proceedings of the 2008 ACM conference on recommender systems.New York:ACM,2008:259-266.
[5]SINHA B,CHANDRA S,GARG M.Development of ontology from Indian agricultural e-governance data using Indo Word Net:a semantic web approach[J].Journal of knowledge management,2015,19(1):25-44.
[6]MAZUMDAR S,CIRAVEGNA F,GENTILE A L,et al.Visualising context and hierarchy in social media[EB/OL].[2017-03-13].http://imash.leeds.ac.uk/event/pdf/Mazumdar_7.pdf.
[7]HEYMANN P,GARCIA-MOLINA H.Collaborative creation of communal hierarchical taxonomies in social tagging systems[EB/OL].[2017-04-03].http://ilpubs.stanford.edu:8090/775/1/2006-10.pdf.
[8]MA F C,LI Y T.Utilising social network analysis to study the characteristics and functions of the co-occurrence network of online tags[J].Journal of online information review,2014,38(2):232-247.
[9]张红,甘利人,薛春香.基于标签聚类的电子商务网站分类目录改善研究[J].现代情报,2012,32(1):3-7.
[10]孙智超.基于知识组织系统社会标注推荐研究[J].图书馆学研究,2016(6):72-79.
[11]滕广青,杨明秋,田依林,等.Folksonomy模式中的知识群落及其核心知识分析[J].图书情报工作,2015,59(22):124-129.
[12]刘雅姝,常志远,姜博,等.标签局部层级的动态演化研究[J].图书馆学研究,2016(13):84-89.
[13]CHAKRABORTY T,GANGULY N,MUKHERJEE A.Rising popularity of interdisciplinary research-an analysis of citation networks[C]//Communication systems and networks(COMSNETS),2014sixth international conference on.New York:IEEE,2014:1-6.
[14]王智博,盛小平,杨洋.基于核心-边缘结构的开放存取期刊评价分析[J].情报理论与实践,2015,38(3):82-85.
[15]WATTS D J,STROGATZ S H.Collective dynamics of‘smallworld’networks[J].Nature,1998,393(6684):440-442.
[16]BURT R S.Positions in networks[J].Journals of social forces,1976,55(1):93-122.
[17]BORGATTI S P,EVERETT M G.Models of core/periphery structures[J].Social networks,1999,21(4):375-395.
[18]滕广青,陈思,常志远,等.基于对应分析的用户与标签间偏好关系研究[J].图书情报工作,2016,60(11):120-127.
[19]叶鹰,张力,赵星,等.用共关键词网络揭示领域知识结构的实验研究[J].情报学报,2012,31(12):1245-1251.
[20]张玥,朱庆华.学术博客交流网络的核心-边缘结构分析实证研究[J].图书情报工作,2009,53(12):25-29.
[21]BORGARRI S P,EVERETT M G.Ecological and perfect colorings[J].Journal of social networks,1994,16(1):43-45.
[22]马费成,刘向.科学知识网络的演化模型[J].系统工程理论与实践,2013,33(2):437-443.
[23]PAGE L,BRIN S,MOTWANI R,et al.The pagerank citation ranking:bringing order to the web[EB/OL].[2017-03-08].http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.206.775&rep=rep1&type=pdf.
[24]GLEICK J.信息简史[M].高博,译.北京:人民邮电出版社,2013:409-421.