基于多特征耦合的数字图书馆知识发现服务优化研究
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摘要
[目的/意义]大数据环境下,用户的知识需求由分散向关联转变,利用多特征耦合可以辅助知识发现服务发现资源间的多种相关关系,从而优化知识发现服务。[方法/过程]通过分析文献内部和外部属性特征定义多特征耦合的概念,从功能角度出发,剖析多特征耦合与数字图书馆知识服务之间的关系,结合现有的知识发现系统构建多特征耦合架构,基于数据层-耦合层-服务层三层提出提升知识发现服务供给侧的方法。[结果/结论]数据层保障数据的质量,数据源由单一向混合转变;耦合层提升耦合分析效果,分析单位由粗向细转变,注重细粒度单元间的语义关联;服务层重视用户的交互体验,开发多维可视化功能。
[Purpose/significance] In the context of big data, the user's knowledge needs are changed from decentralization to correlation, and multi-feature coupling is used to assist the knowledge discovery service to discover multiple correlations between resources, thereby optimizing knowledge discovery services. [Method/process] The concept of multi-feature coupling was defined by analyzing the internal and external attribute characteristics of the literature. This paper analyzed the relationship between multi-feature coupling and digital library knowledge service according to the function of multi-feature coupling. Then, by combining the existing knowledge discovery system, the multi-feature coupling structure was constructed. And the method of improving the supply side of the knowledge discovery service was proposed based on data layer-coupling layer-service layer. [Result/conclusion] The data layer guarantees the quality of the data, the data source changes from single to mixed; the coupling layer enhances the effect of coupling analysis, the unit of analysis changes from coarse-grained to fine-grained, the semantic association between fine-grained units attracts much attention; the service layer attaches importance to the user's interactive experience and develops multi-dimensional visualization function.
[Purpose/significance] In the context of big data, the user's knowledge needs are changed from decentralization to correlation, and multi-feature coupling is used to assist the knowledge discovery service to discover multiple correlations between resources, thereby optimizing knowledge discovery services. [Method/process] The concept of multi-feature coupling was defined by analyzing the internal and external attribute characteristics of the literature. This paper analyzed the relationship between multi-feature coupling and digital library knowledge service according to the function of multi-feature coupling. Then, by combining the existing knowledge discovery system, the multi-feature coupling structure was constructed. And the method of improving the supply side of the knowledge discovery service was proposed based on data layer-coupling layer-service layer. [Result/conclusion] The data layer guarantees the quality of the data, the data source changes from single to mixed; the coupling layer enhances the effect of coupling analysis, the unit of analysis changes from coarse-grained to fine-grained, the semantic association between fine-grained units attracts much attention; the service layer attaches importance to the user's interactive experience and develops multi-dimensional visualization function.
引文
[1]卢章平,袁润,王正兴.发现服务:大学与研究机构图书馆的趋势[J].中国图书馆学报,2014,40(3):20-26.
[2]夏立新,白阳,张心怡.融合与重构:智慧图书馆发展新形态[J].中国图书馆学报,2018,44(1):35-49.
[3]舍恩伯格,库克耶.大数据时代:生活、工作与思维的大变革[M].盛杨燕,周涛,译.杭州:浙江人民出版社,2013.
[4]邱均平.信息计量学[M].武汉:武汉大学出版社,2007.
[5]EGGHE L,ROUSSEAU R.Cocitation,bibliographic coupling and a characterization of lattice citation networks[J].Scientometrics,2002,55(3):349-361.
[6]KESSLER M.Bibliographic coupling between scientific papers[J].American documentation,1963(14):123-131.
[7]BAEERCOULARD E,LELU A,ZITT M.Mapping none sciences by citation flows:a preliminary analysis[J].Scaentometrics,2007,70(3):859-880.
[8]王洵.开斯勒与“文献合配”[J].情报科学,1981,2(4):29-32.
[9]邱均平.论“引文耦合”与“同被引”[J].图书馆,1987(3):13-19.
[10]张郁蔚.以直接引用、书目耦合及共同作者探讨图书资讯学跨学科之变迁[D].台北:台湾大学,2009.
[11]邱均平,王菲菲.基于共现与耦合的馆藏文献资源深度聚合研究探析[J].中国图书馆学报,2013,39(3):25-33.
[12]MORRIS S A.Unified mathematical treatment of complex cascaded bipartite networks:the case of collections of journal papers[D].Stillwater:Oklahoma State University.2005.
[13]李洁,毕强,张晗,等.数据驱动下数字图书馆知识发现的服务研究[J].情报资料工作,2018(4):6-14.
[14]彭佳,郑巧英.信息资源聚合与组织研究---以发现系统为例[J].图书馆杂志,2016,35(3):80-85.
[15]曾建勋,丁遒劲.基于语义的国家科技信息发现服务体系研究[J].中国图书馆学报,2017,43(4):51-62.
[16]崔金栋,孙遥遥,郑鹊,等.我国政务微博社会网络特征对比分析实证研究[J].情报科学,2016,34(12):120-126,132.
[17]毕强,闫晶,李洁.大数据时代数字图书馆服务转型面临的新形势与新要求[J].情报理论与实践,2017,40(12):12-16,5.
[18]董克.数字文献资源多元深度聚合研究[D].武汉:武汉大学,2014.
[19]郭秋萍,梁梦丽,刘秀丽,等.基于作者-关键词-引文多重共现的超网络知识关联研究[J].情报理论与实践,2016,39(7):20-26.
[20]任红娟.一种内容和引用特征融合的知识结构划分方法研究[J].中国图书馆学报,2013,39(5):76-82.
[21]王福.基于信息资源组织视觉的新型OPAC系统设计研究[J].图书馆工作与研究,2015(3):38-40.
[22]陈为,沈则潜,陶煜波.数据可视化[M].北京:电子工业出版社,2013.
[23]RICHARD K,KEVIN W B.Using global mapping to create more accurate document-level maps of research fields[J].Journal of the American Society for Information Science and Technology,2011,62(1):1-18.
[2]夏立新,白阳,张心怡.融合与重构:智慧图书馆发展新形态[J].中国图书馆学报,2018,44(1):35-49.
[3]舍恩伯格,库克耶.大数据时代:生活、工作与思维的大变革[M].盛杨燕,周涛,译.杭州:浙江人民出版社,2013.
[4]邱均平.信息计量学[M].武汉:武汉大学出版社,2007.
[5]EGGHE L,ROUSSEAU R.Cocitation,bibliographic coupling and a characterization of lattice citation networks[J].Scientometrics,2002,55(3):349-361.
[6]KESSLER M.Bibliographic coupling between scientific papers[J].American documentation,1963(14):123-131.
[7]BAEERCOULARD E,LELU A,ZITT M.Mapping none sciences by citation flows:a preliminary analysis[J].Scaentometrics,2007,70(3):859-880.
[8]王洵.开斯勒与“文献合配”[J].情报科学,1981,2(4):29-32.
[9]邱均平.论“引文耦合”与“同被引”[J].图书馆,1987(3):13-19.
[10]张郁蔚.以直接引用、书目耦合及共同作者探讨图书资讯学跨学科之变迁[D].台北:台湾大学,2009.
[11]邱均平,王菲菲.基于共现与耦合的馆藏文献资源深度聚合研究探析[J].中国图书馆学报,2013,39(3):25-33.
[12]MORRIS S A.Unified mathematical treatment of complex cascaded bipartite networks:the case of collections of journal papers[D].Stillwater:Oklahoma State University.2005.
[13]李洁,毕强,张晗,等.数据驱动下数字图书馆知识发现的服务研究[J].情报资料工作,2018(4):6-14.
[14]彭佳,郑巧英.信息资源聚合与组织研究---以发现系统为例[J].图书馆杂志,2016,35(3):80-85.
[15]曾建勋,丁遒劲.基于语义的国家科技信息发现服务体系研究[J].中国图书馆学报,2017,43(4):51-62.
[16]崔金栋,孙遥遥,郑鹊,等.我国政务微博社会网络特征对比分析实证研究[J].情报科学,2016,34(12):120-126,132.
[17]毕强,闫晶,李洁.大数据时代数字图书馆服务转型面临的新形势与新要求[J].情报理论与实践,2017,40(12):12-16,5.
[18]董克.数字文献资源多元深度聚合研究[D].武汉:武汉大学,2014.
[19]郭秋萍,梁梦丽,刘秀丽,等.基于作者-关键词-引文多重共现的超网络知识关联研究[J].情报理论与实践,2016,39(7):20-26.
[20]任红娟.一种内容和引用特征融合的知识结构划分方法研究[J].中国图书馆学报,2013,39(5):76-82.
[21]王福.基于信息资源组织视觉的新型OPAC系统设计研究[J].图书馆工作与研究,2015(3):38-40.
[22]陈为,沈则潜,陶煜波.数据可视化[M].北京:电子工业出版社,2013.
[23]RICHARD K,KEVIN W B.Using global mapping to create more accurate document-level maps of research fields[J].Journal of the American Society for Information Science and Technology,2011,62(1):1-18.