共现科学知识图谱构建技术与工具研究
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摘要
[目的/意义]共现科学知识图谱在研究热点与趋势洞察、学术共同体发现、学科交叉融合的测度与可视化等方面扮演愈加重要的角色,有必要深入探究其构建技术与工具。[研究设计/方法]将共现网络知识图谱构建流程划分为知识单元抽取、知识网络构建、知识发现与可视化三个层次,结合主流共现图谱软件系统梳理各层次涉及的关键技术,并基于行动者、事件和转换方式三大维度构建具有普适性的共现网络构建模型。[结论/发现]知识单元选择的细粒度、客观性与创新性;共现网络构建的差异化、语义化和多元化;统计分析方法的改进以及不同图谱科学结构揭示能力的比较是共现科学知识图谱研究与应用的发展趋势和主要挑战。[创新/价值]对共现图谱构建的理论基础和工具进行了详细梳理,提出了共现网络构建模型和未来发展方向。
[Purpose/Significance] Mapping knowledge domain of co-occurrence science plays an increasingly important role in the study of detecting research hotspots and trends,discovering academic community,measuring and visualizing interdisciplinary integration and so on. So it is necessary to profoundly explore its key techniques and tools.[Design/Methodology]This paper divides the process of mapping knowledge domain construction in co-occurrence science into three levels: knowledge unit extraction,knowledge network construction,and knowledge discovery and visualization,and analyzes the key technologies according to some main co-occurrence mapping softwares. Then a co-occurrence network construction model with wide adaptability is proposed based on the actors,events and transforming methods.[Findings/Conclusion] The developing trends and major chal enges have been pointed out,including the fine granularity,objectivity and innovation of knowledge unit selection; the differentiation,semantics and diversity of co-occurrence network construction; the improvement of statistical analyzing methods and the comparative study on revealing ability of different map scientific structures.[Originality/Value]Theories and tools of co-occurrence map construction have been thoroughly analyzed in details,and the co-occurrence network construction model and the developing trends have been put forward.
[Purpose/Significance] Mapping knowledge domain of co-occurrence science plays an increasingly important role in the study of detecting research hotspots and trends,discovering academic community,measuring and visualizing interdisciplinary integration and so on. So it is necessary to profoundly explore its key techniques and tools.[Design/Methodology]This paper divides the process of mapping knowledge domain construction in co-occurrence science into three levels: knowledge unit extraction,knowledge network construction,and knowledge discovery and visualization,and analyzes the key technologies according to some main co-occurrence mapping softwares. Then a co-occurrence network construction model with wide adaptability is proposed based on the actors,events and transforming methods.[Findings/Conclusion] The developing trends and major chal enges have been pointed out,including the fine granularity,objectivity and innovation of knowledge unit selection; the differentiation,semantics and diversity of co-occurrence network construction; the improvement of statistical analyzing methods and the comparative study on revealing ability of different map scientific structures.[Originality/Value]Theories and tools of co-occurrence map construction have been thoroughly analyzed in details,and the co-occurrence network construction model and the developing trends have been put forward.
引文
1 Price D J.Networks of Scientific Papers[J].Science,1965,149(3683):510-515.
2 Small H.Co-citation in the Scientific Literature:A New Measure of the Relationship between Two Documents[J].Journal of the American Society for Information Science&Technology,1973,24(4):265-269.
3 Callon M,Courtial J J P,Turner W A,et al.From Translations to Problematic Networks-An Introduction to Co-word A-nalysis.Soc Sci Inf Sur Les Sci Soc[J].Social Science Information,1983,22(2):191-235.
4 Peters H P F,Raan A F J V.Structuring Scientific Activities by Co-author Analysis[J].Scientometrics,1991,20(1):235-255.
5陈悦,刘则渊.悄然兴起的科学知识图谱[J].科学学研究,2005,23(2):149-154.
6李明鑫,王松.近十年国内知识图谱研究脉络及主题分析[J].图书情报知识,2016(4):93-101.
7王发明,朱美娟.国内区块链研究热点的文献计量分析[J].情报杂志,2017(12):69-74.
8赵蓉英,魏明坤.基于可视化图谱的国内外大数据研究[J].情报科学,2016,34(12):3-10.
9 Shiffrin R M,B9rner K.Mapping Knowledge Domains[J].Proc Natl Acad Sci U S A,2004,101(Supplement 1):5183-5185.
10曹树金,吴育冰,韦景竹,等.知识图谱研究的脉络、流派与趋势---基于SSCI与CSSCI期刊论文的计量与可视化[J].中国图书馆学报,2015,41(5):16-34.
11 Chen C.Science Mapping:A Systematic Review of the Literature[J].Journal of Data and Information Science,2017,2(2):1-40.
12 Bishop A P.Digital Libraries and Knowledge Disaggregation:the Use of Journal Article Components[C]//ACM Conference on Digital Libraries.ACM,1998:29-39.
13曹树金,李洁娜,王志红.面向网络信息资源聚合搜索的细粒度聚合单元元数据研究[J].中国图书馆学报,2017,43(4):74-92.
14 Sugimoto C R,Mccain K W.Visualizing Changes over Time:A History of Information Retrieval through the Lens of Descriptor Tri-Occurrence Mapping.[J].Journal of Information Science,2010,36(4):481-493.
15杨立英.科技论文共现理论研究与应用[D].中国科学院文献情报中心,2007.
16张超星,刘小玲,谭宗颖.图情领域的大共现及其发展现状[J].情报资料工作,2016,37(1):27-33.
17 B9rner K,Chen C,Boyack K W.Visualizing Knowledge Domains[J].Annual Review of Information Science&Technology,2003,37(1):179-255.
18杨思洛,韩瑞珍.国外知识图谱绘制的方法与工具分析[J].图书情报知识,2012(6):101-109.
19 Cobo M J,Herrera-Viedma E,Herrera F.Science Mapping Software Tools:Review,Analysis,and Cooperative Study among Tools[J].Journal of the Association for Information Science&Technology,2014,62(7):1382-1402.
20杨萌,张云中.知识地图、科学知识图谱和谷歌知识图谱的分歧和交互[J].情报理论与实践,2017,40(5):122-126.
21 Harzing A W,Alakangas S.Google Scholar,Scopus and the Web of Science:A longitudinal and cross-disciplinary comparison[J].Scientometrics,2016,106(2):787-804.
22孙建军.链接分析:知识基础、研究主体、研究热点与前沿综述---基于科学知识图谱的途径[J].情报学报,2014,33(6):659-672.
23邱均平,温芳芳.近五年来图书情报学研究热点与前沿的可视化分析---基于13种高影响力外文源刊的计量研究[J].中国图书馆学报,2011,37(2):51-60.
24潘有能,谭健.普赖斯奖得主的科学合作网络研究[J].图书情报工作,2012,56(16):80-84.
25 Zhu Y,Yan E.Dynamic Subfield Analysis of Disciplines:An Examination of the Trading Impact and Knowledge Diffusion Patterns of Computer Science[J].Scientometrics,2015,104(1):335-359.
26潘玮,牟冬梅,李茵,等.关键词共现方法识别领域研究热点过程中的数据清洗方法[J].图书情报工作,2017,61(7):111-117.
27李纲,巴志超.共词分析过程中的若干问题研究[J].中国图书馆学报,2017,43(4):93-113.
28 Aria M,Cuccurullo C.Bibliometrix:An R-Tool for Comprehensive Science Mapping Analysis[J].Journal of Informetrics,2017,11(4):959-975.
29 Eck N J V,Waltman L.How to Normalize Cooccurrence Data?An Analysis of Some Well‐known Similarity Measures[J].Journal of the Association for Information Science&Technology,2010,60(8):1635-1651.
30吴清强,赵亚娟.基于论文属性的加权共词模型探讨[J].情报学报,2008,27(1):89-92.
31朱丽娟,于建荣.合著关系网络的加权模式研究[J].图书情报工作,2010,54(12):69-73.
32唐晓波,肖璐.融合关键词增补与领域本体的共词分析方法研究[J].现代图书情报技术,2013,29(11):60-67.
33王玉林,王忠义.细粒度语义共词分析方法研究[J].图书情报工作,2014,58(21):73-80.
34徐硕,乔晓东,朱礼军,等.共现聚类分析的新方法:最大频繁项集挖掘[J].情报学报,2012,31(2):143-150.
35刘勇,杜一.网络数据可视化与分析利器:Gephi中文教程[M].北京:电子工业出版社,2017:3-4.
36 Eck N J V,Waltman L.Visualizing Bibliometric Networks[M]//Measuring Scholarly Impact.Springer International Publishing,2014:285-320.
37 Wilkinson L.The Grammar of Graphics[M].Springer,2005:85-356.
38哈德利·威克姆.ggplot2:数据分析与图形艺术[M].西安交通大学出版社,2013:3-4.
39 Ognyanova K.Network Visualization with R[EB/OL].[2018-06-22].http://kateto.net/network-visualization.
40傅柱,王曰芬.共词分析中术语收集阶段的若干问题研究[J].情报学报,2016,35(7):704-713.
41张洋,谢卓力.基于多源网络学术信息聚合的知识图谱构建研究[J].图书情报工作,2014,58(22):84-94.
42商宪丽,王学东,张煜轩.基于标签共现的学术博客知识资源聚合研究[J].情报科学,2016,V34(5):125-129.
43巴志超,李纲,朱世伟.共现分析中的关键词选择与语义度量方法研究[J].情报学报,2016,35(2):197-207.
44王忠义,谭旭,夏立新.共词分析方法的细粒度化与语义化研究[J].情报学报,2014(9):969-978.
45 Perianes-Rodriguez A,Waltman L,Eck N J V.Constructing Bibliometric Networks:A Comparison between Full and Fractional Counting[J].Journal of Informetrics,2016,10(4):1178-1195.
46党永杰,邱均平,郑世珏.基于改进BA模型的作者合作加权网络动态演化研究[J].情报学报,2017,36(1):28-38.
47 Small H.Tracking and Predicting Growth Areas in Science[J].Scientometrics,2006,68(3):595-610.
48 White H D.Author Cocitation Analysis and Pearson's[M].John Wiley&Sons,Inc.2003.
49 Leydesdorff L,Vaughan L.Co-occurrence Matrices and Their Applications in Information Science:Extending ACA to the Web Environment[M].John Wiley&Sons,Inc.2006.
50崔雷,隋明爽.共现聚类分析结果表达方法的研究[J].情报学报,2015,34(12):1270-1277.
51邱均平,董克.作者共现网络的科学研究结构揭示能力比较研究[J].中国图书馆学报,2014,40(1):15-24.
52 Kostoff R N.Multidisciplinary Research Thrusts from Co-word Analysis[C]//Technology Management:the New International Language.IEEE,2002.
53刘则渊,陈悦,侯海燕.科学知识图谱:方法与应用[M].北京:人民出版社,2008:3-5.
54刘则渊,陈超美,侯海燕,等.迈向科学学大变革的时代[J].科学学与科学技术管理,2009,30(7):5-12.
2 Small H.Co-citation in the Scientific Literature:A New Measure of the Relationship between Two Documents[J].Journal of the American Society for Information Science&Technology,1973,24(4):265-269.
3 Callon M,Courtial J J P,Turner W A,et al.From Translations to Problematic Networks-An Introduction to Co-word A-nalysis.Soc Sci Inf Sur Les Sci Soc[J].Social Science Information,1983,22(2):191-235.
4 Peters H P F,Raan A F J V.Structuring Scientific Activities by Co-author Analysis[J].Scientometrics,1991,20(1):235-255.
5陈悦,刘则渊.悄然兴起的科学知识图谱[J].科学学研究,2005,23(2):149-154.
6李明鑫,王松.近十年国内知识图谱研究脉络及主题分析[J].图书情报知识,2016(4):93-101.
7王发明,朱美娟.国内区块链研究热点的文献计量分析[J].情报杂志,2017(12):69-74.
8赵蓉英,魏明坤.基于可视化图谱的国内外大数据研究[J].情报科学,2016,34(12):3-10.
9 Shiffrin R M,B9rner K.Mapping Knowledge Domains[J].Proc Natl Acad Sci U S A,2004,101(Supplement 1):5183-5185.
10曹树金,吴育冰,韦景竹,等.知识图谱研究的脉络、流派与趋势---基于SSCI与CSSCI期刊论文的计量与可视化[J].中国图书馆学报,2015,41(5):16-34.
11 Chen C.Science Mapping:A Systematic Review of the Literature[J].Journal of Data and Information Science,2017,2(2):1-40.
12 Bishop A P.Digital Libraries and Knowledge Disaggregation:the Use of Journal Article Components[C]//ACM Conference on Digital Libraries.ACM,1998:29-39.
13曹树金,李洁娜,王志红.面向网络信息资源聚合搜索的细粒度聚合单元元数据研究[J].中国图书馆学报,2017,43(4):74-92.
14 Sugimoto C R,Mccain K W.Visualizing Changes over Time:A History of Information Retrieval through the Lens of Descriptor Tri-Occurrence Mapping.[J].Journal of Information Science,2010,36(4):481-493.
15杨立英.科技论文共现理论研究与应用[D].中国科学院文献情报中心,2007.
16张超星,刘小玲,谭宗颖.图情领域的大共现及其发展现状[J].情报资料工作,2016,37(1):27-33.
17 B9rner K,Chen C,Boyack K W.Visualizing Knowledge Domains[J].Annual Review of Information Science&Technology,2003,37(1):179-255.
18杨思洛,韩瑞珍.国外知识图谱绘制的方法与工具分析[J].图书情报知识,2012(6):101-109.
19 Cobo M J,Herrera-Viedma E,Herrera F.Science Mapping Software Tools:Review,Analysis,and Cooperative Study among Tools[J].Journal of the Association for Information Science&Technology,2014,62(7):1382-1402.
20杨萌,张云中.知识地图、科学知识图谱和谷歌知识图谱的分歧和交互[J].情报理论与实践,2017,40(5):122-126.
21 Harzing A W,Alakangas S.Google Scholar,Scopus and the Web of Science:A longitudinal and cross-disciplinary comparison[J].Scientometrics,2016,106(2):787-804.
22孙建军.链接分析:知识基础、研究主体、研究热点与前沿综述---基于科学知识图谱的途径[J].情报学报,2014,33(6):659-672.
23邱均平,温芳芳.近五年来图书情报学研究热点与前沿的可视化分析---基于13种高影响力外文源刊的计量研究[J].中国图书馆学报,2011,37(2):51-60.
24潘有能,谭健.普赖斯奖得主的科学合作网络研究[J].图书情报工作,2012,56(16):80-84.
25 Zhu Y,Yan E.Dynamic Subfield Analysis of Disciplines:An Examination of the Trading Impact and Knowledge Diffusion Patterns of Computer Science[J].Scientometrics,2015,104(1):335-359.
26潘玮,牟冬梅,李茵,等.关键词共现方法识别领域研究热点过程中的数据清洗方法[J].图书情报工作,2017,61(7):111-117.
27李纲,巴志超.共词分析过程中的若干问题研究[J].中国图书馆学报,2017,43(4):93-113.
28 Aria M,Cuccurullo C.Bibliometrix:An R-Tool for Comprehensive Science Mapping Analysis[J].Journal of Informetrics,2017,11(4):959-975.
29 Eck N J V,Waltman L.How to Normalize Cooccurrence Data?An Analysis of Some Well‐known Similarity Measures[J].Journal of the Association for Information Science&Technology,2010,60(8):1635-1651.
30吴清强,赵亚娟.基于论文属性的加权共词模型探讨[J].情报学报,2008,27(1):89-92.
31朱丽娟,于建荣.合著关系网络的加权模式研究[J].图书情报工作,2010,54(12):69-73.
32唐晓波,肖璐.融合关键词增补与领域本体的共词分析方法研究[J].现代图书情报技术,2013,29(11):60-67.
33王玉林,王忠义.细粒度语义共词分析方法研究[J].图书情报工作,2014,58(21):73-80.
34徐硕,乔晓东,朱礼军,等.共现聚类分析的新方法:最大频繁项集挖掘[J].情报学报,2012,31(2):143-150.
35刘勇,杜一.网络数据可视化与分析利器:Gephi中文教程[M].北京:电子工业出版社,2017:3-4.
36 Eck N J V,Waltman L.Visualizing Bibliometric Networks[M]//Measuring Scholarly Impact.Springer International Publishing,2014:285-320.
37 Wilkinson L.The Grammar of Graphics[M].Springer,2005:85-356.
38哈德利·威克姆.ggplot2:数据分析与图形艺术[M].西安交通大学出版社,2013:3-4.
39 Ognyanova K.Network Visualization with R[EB/OL].[2018-06-22].http://kateto.net/network-visualization.
40傅柱,王曰芬.共词分析中术语收集阶段的若干问题研究[J].情报学报,2016,35(7):704-713.
41张洋,谢卓力.基于多源网络学术信息聚合的知识图谱构建研究[J].图书情报工作,2014,58(22):84-94.
42商宪丽,王学东,张煜轩.基于标签共现的学术博客知识资源聚合研究[J].情报科学,2016,V34(5):125-129.
43巴志超,李纲,朱世伟.共现分析中的关键词选择与语义度量方法研究[J].情报学报,2016,35(2):197-207.
44王忠义,谭旭,夏立新.共词分析方法的细粒度化与语义化研究[J].情报学报,2014(9):969-978.
45 Perianes-Rodriguez A,Waltman L,Eck N J V.Constructing Bibliometric Networks:A Comparison between Full and Fractional Counting[J].Journal of Informetrics,2016,10(4):1178-1195.
46党永杰,邱均平,郑世珏.基于改进BA模型的作者合作加权网络动态演化研究[J].情报学报,2017,36(1):28-38.
47 Small H.Tracking and Predicting Growth Areas in Science[J].Scientometrics,2006,68(3):595-610.
48 White H D.Author Cocitation Analysis and Pearson's[M].John Wiley&Sons,Inc.2003.
49 Leydesdorff L,Vaughan L.Co-occurrence Matrices and Their Applications in Information Science:Extending ACA to the Web Environment[M].John Wiley&Sons,Inc.2006.
50崔雷,隋明爽.共现聚类分析结果表达方法的研究[J].情报学报,2015,34(12):1270-1277.
51邱均平,董克.作者共现网络的科学研究结构揭示能力比较研究[J].中国图书馆学报,2014,40(1):15-24.
52 Kostoff R N.Multidisciplinary Research Thrusts from Co-word Analysis[C]//Technology Management:the New International Language.IEEE,2002.
53刘则渊,陈悦,侯海燕.科学知识图谱:方法与应用[M].北京:人民出版社,2008:3-5.
54刘则渊,陈超美,侯海燕,等.迈向科学学大变革的时代[J].科学学与科学技术管理,2009,30(7):5-12.