基于文献多属性加权的共词分析方法研究
|
摘要
【目的/意义】共词分析法是文献情报分析的重要方法,对促进学科领域等的研究和发展具有重要作用。针对共词分析法中存在的文献层面和词层面"同量不同质"问题、高频孤立词问题等,提出一种基于文献多属性加权的共词分析方法。【方法/过程】该方法利用文献发表时间、被引次数和下载量等属性来度量文献时效性和被关注度,以表征文献层面的权重;利用文献标题和摘要等属性对文献关键词的差异性进行度量;综合文献权重和词差异性权重对共词分析词频次及共词对频次进行加权处理,然后依据二者加权后的频次确定共词分析用词集合及构建共词矩阵。【结果/结论】以CNKI数据库有关主题模型研究的核心期刊论文为数据源,对该领域的研究主题热点进行分析,从共词分析用词选择和聚类分析等方面与一般共词分析法进行对比,验证了本文所提加权方法具有一定的合理性和有效性。
【Purpose/significance] Co-word analysis is an important method for literature information research, which is of great significance to discipline development. However, the method has the problem of different quality with the same quantity both in document level and word level and the problem of high-frequency isolated word.【Method/process] This paper proposes a weighted co-word analysis method based on multi attributes of literature, which uses literature publication time to measure timeliness and uses literature citation times and downloads to measure attention degree, and then uses the two indicators to measure the weight of a literature. Moreover, the importance of each word is measured by the literature's title and abstract. Then, take the literature weight and word importance to improve the general co-word analysis method by weighted co-word frequency calculation and chosen co-word matrix construction.【Result/conclusion] In case of Topic Model research, this paper analyzes the domain research topic and hotspot based on the data collected from CNKI database and the result shows, compared with general co-word analysis method, the improved method is proved to be some reasonable and effective at word choice and co-word clustering analysis.
【Purpose/significance] Co-word analysis is an important method for literature information research, which is of great significance to discipline development. However, the method has the problem of different quality with the same quantity both in document level and word level and the problem of high-frequency isolated word.【Method/process] This paper proposes a weighted co-word analysis method based on multi attributes of literature, which uses literature publication time to measure timeliness and uses literature citation times and downloads to measure attention degree, and then uses the two indicators to measure the weight of a literature. Moreover, the importance of each word is measured by the literature's title and abstract. Then, take the literature weight and word importance to improve the general co-word analysis method by weighted co-word frequency calculation and chosen co-word matrix construction.【Result/conclusion] In case of Topic Model research, this paper analyzes the domain research topic and hotspot based on the data collected from CNKI database and the result shows, compared with general co-word analysis method, the improved method is proved to be some reasonable and effective at word choice and co-word clustering analysis.
引文
1 He Q. Knowledge Discovery through Co-Word Analysis[J]. Library Trends, 1999, 48(1):133-59.
2 冯璐,冷伏海.共词分析方法理论进展[J].中国图书馆学报,2006,32(2):88-92.
3 唐果媛,张薇.国内外共词分析法研究的发展与分析[J].图书情报工作,2014,58(22):138-145.
4 张刚要.基于共词分析的教育技术学学科结构可视化研究[J].中国电化教育, 2013,34(2):6-11.
5 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.
6 Wang X, Liu J, Sheng F. Analysis of Hotspots in the Field of Domestic Knowledge Discovery Based on Co-word Analysis Method[J]. Cybernetics&Information Technologies, 2014, 14(5):145-158.
7 王米雪,张立国.我国智慧教育领域的研究热点与发展趋势分析——基于词频分析法,共词聚类法和多维尺度分析法[J].现代教育技术, 2017, 27(3):41-48.
8 MLA Wu C C, Leu H J. Examining the trends of technological development in hydrogen energy using patent co-word map analysis[J]. International Journal of Hydrogen Energy, 2014, 39(33):19262-19269.
9 唐果媛,张薇.基于共词分析法的学科主题演化研究进展与分析[J].图书情报工作,2015,59(5):128-136.
10 Wu Y, Jin X, Xue Y. Evaluation of research topic evolution in psychiatry using co-word analysis[J]. Medicine,2017, 96(25):e7349-e7355.
11 杨彦荣,张阳.加权共词分析法研究[J].情报理论与实践,2011,34(4):61-63.
12 闵波,王坤,杜冰,等.文章发表时间对生物医学文献知识发现的影响[J].中华医学图书情报杂志, 2017, 26(5):49-52.
13 Ravikumar S, Agrahari A, Singh S N. Mapping the intellectual structure of scientometrics:A co-word analysis of the journal Scientometrics(2005–2010)[J]. Scientometrics,2015, 102(1):929-955.
14 李纲,李轶.一种基于关键词加权的共词分析方法[J].情报科学,2011,29(3):321-324.
15 钟伟金,李佳.共词分析法研究(一)——共词分析的过程与方式[J].情报杂志,2008, 27(5):70-72.
16 王飒,包丽颖.基于文献计量的共词分析方法及应用述评[J].情报科学, 2014,32(4):150-154.
17 李纲,王忠义.基于语义的共词分析方法研究[J].情报杂志, 2011, 30(12):145-149.
18 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.
19 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.
20 钟伟金.基于主要主题词加权的共词聚类分析法效果研究[J].情报学报,2009,28(2):214-219.
21 Su Y M, Hsu P Y, Pai N Y. An approach to discover and recommend cross-domain bridge-keywords in document banks[J]. Electronic Library, 2010, 28(5):669-687.
22 陈慧茹,肖相泽,冯锋.科技创新政策加权共词网络研究——基于扎根理论与政策测量[J].科学学研究, 2016,34(12):1769-1776.
23 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.
24 刘乔,刘彬.基于时间加权的协同过滤推荐算法的改进[J].计算机工程与设计,2016,37(7):1827-1830.
25 郭强,赵瑾.基于被引次数的论文影响力下载类指标研究[J].图书馆理论与实践,2014,36(11):50-54.
26 杨春华,王桂枝,马红月.换个角度看服务:从下载量看图书馆学论文的价值与需求[J].图书与情报, 2010,154(4):100-103.
27 廖晓,李志宏,席运江.基于加权知识网络的企业社区用户创新知识建模及分析方法[J].系统工程理论与实践,2016, 36(1):94-105.
28 Seo J, Lee J Y, Ahn S, et al. Keyword Hierarchy Construction Using Co-Word Analysis[J]. International Information Institute(Tokyo). Information, 2016, 19(6B):2397-2402.
2 冯璐,冷伏海.共词分析方法理论进展[J].中国图书馆学报,2006,32(2):88-92.
3 唐果媛,张薇.国内外共词分析法研究的发展与分析[J].图书情报工作,2014,58(22):138-145.
4 张刚要.基于共词分析的教育技术学学科结构可视化研究[J].中国电化教育, 2013,34(2):6-11.
5 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.
6 Wang X, Liu J, Sheng F. Analysis of Hotspots in the Field of Domestic Knowledge Discovery Based on Co-word Analysis Method[J]. Cybernetics&Information Technologies, 2014, 14(5):145-158.
7 王米雪,张立国.我国智慧教育领域的研究热点与发展趋势分析——基于词频分析法,共词聚类法和多维尺度分析法[J].现代教育技术, 2017, 27(3):41-48.
8 MLA Wu C C, Leu H J. Examining the trends of technological development in hydrogen energy using patent co-word map analysis[J]. International Journal of Hydrogen Energy, 2014, 39(33):19262-19269.
9 唐果媛,张薇.基于共词分析法的学科主题演化研究进展与分析[J].图书情报工作,2015,59(5):128-136.
10 Wu Y, Jin X, Xue Y. Evaluation of research topic evolution in psychiatry using co-word analysis[J]. Medicine,2017, 96(25):e7349-e7355.
11 杨彦荣,张阳.加权共词分析法研究[J].情报理论与实践,2011,34(4):61-63.
12 闵波,王坤,杜冰,等.文章发表时间对生物医学文献知识发现的影响[J].中华医学图书情报杂志, 2017, 26(5):49-52.
13 Ravikumar S, Agrahari A, Singh S N. Mapping the intellectual structure of scientometrics:A co-word analysis of the journal Scientometrics(2005–2010)[J]. Scientometrics,2015, 102(1):929-955.
14 李纲,李轶.一种基于关键词加权的共词分析方法[J].情报科学,2011,29(3):321-324.
15 钟伟金,李佳.共词分析法研究(一)——共词分析的过程与方式[J].情报杂志,2008, 27(5):70-72.
16 王飒,包丽颖.基于文献计量的共词分析方法及应用述评[J].情报科学, 2014,32(4):150-154.
17 李纲,王忠义.基于语义的共词分析方法研究[J].情报杂志, 2011, 30(12):145-149.
18 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.
19 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.
20 钟伟金.基于主要主题词加权的共词聚类分析法效果研究[J].情报学报,2009,28(2):214-219.
21 Su Y M, Hsu P Y, Pai N Y. An approach to discover and recommend cross-domain bridge-keywords in document banks[J]. Electronic Library, 2010, 28(5):669-687.
22 陈慧茹,肖相泽,冯锋.科技创新政策加权共词网络研究——基于扎根理论与政策测量[J].科学学研究, 2016,34(12):1769-1776.
23 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.
24 刘乔,刘彬.基于时间加权的协同过滤推荐算法的改进[J].计算机工程与设计,2016,37(7):1827-1830.
25 郭强,赵瑾.基于被引次数的论文影响力下载类指标研究[J].图书馆理论与实践,2014,36(11):50-54.
26 杨春华,王桂枝,马红月.换个角度看服务:从下载量看图书馆学论文的价值与需求[J].图书与情报, 2010,154(4):100-103.
27 廖晓,李志宏,席运江.基于加权知识网络的企业社区用户创新知识建模及分析方法[J].系统工程理论与实践,2016, 36(1):94-105.
28 Seo J, Lee J Y, Ahn S, et al. Keyword Hierarchy Construction Using Co-Word Analysis[J]. International Information Institute(Tokyo). Information, 2016, 19(6B):2397-2402.