基于维基百科的计算机科学领域本体网络结构研究
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摘要
基于维基百科的类别信息获取概念及概念关系,将提取的概念和关系映射到OWL语言以此构建计算机科学领域本体及其本体网络。在此基础上,利用社会网络分析法分析了文章构建的领域本体的网络结构信息。基于维基百科构建的本体网络有"较小的平均路径长度""较小的聚类系数""符合幂率分布"等特点,属于无标度网络。基于维基百科构建本体属于本体半自动构建的方法,抽取的概念关系不够丰富,但该方法能够为充分挖掘本体的语义信息,发现本体中的隐含知识,解决领域知识的共享等问题提供方法和参考。
In this paper,we map the concepts and relationships extracted from classification information on Wikipedia to OWL language in order to build the domain ontology and ontology network of computer science. On this basis,the paper analyzes the network structure information of the domain ontology by social network analysis method. The ontology network constructed in this paper has the characteristics of "small average path length""small clustering coefficient"and "consistent power distribution",which belong to the scale free network. The method of constructing ontology based on Wikipedia belongs to the semi-automatic construction method of ontology,in which the concept relationships are not rich enough,but this method provides references for fully mining the semantic information of ontology,finding the implicit knowledge in ontology,solving the problem of domain knowledge sharing and so on.
In this paper,we map the concepts and relationships extracted from classification information on Wikipedia to OWL language in order to build the domain ontology and ontology network of computer science. On this basis,the paper analyzes the network structure information of the domain ontology by social network analysis method. The ontology network constructed in this paper has the characteristics of "small average path length""small clustering coefficient"and "consistent power distribution",which belong to the scale free network. The method of constructing ontology based on Wikipedia belongs to the semi-automatic construction method of ontology,in which the concept relationships are not rich enough,but this method provides references for fully mining the semantic information of ontology,finding the implicit knowledge in ontology,solving the problem of domain knowledge sharing and so on.
引文
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[19]CORRE P,et al.A multi-ontology approach to annotate scientific documents based on a modularization technique[J].Journal of Biomedical Informatics,2015,58:208-219.
[20]SASSON E,et al.Improving similarity measures of relatedness proximity:toward augmented concept maps[J].Journal of Informetrics,2015,9(3):618-628.
[21]杨健.基于No SQL的本体存储与查询研究[D].重庆:重庆大学,2015.
[22]DAVOODI E,et al.A semantic social network-based expert recommender system[J].Applied Intelligence,2013,39(1):1-13.
[23]YOO D,et al.An ontology-based co-creation enhancing system for idea recommendation in an online community[J].Data Base for Advances in Information Systems,2015,46(3):9-22.
[24]梁帅,等.本体结构特征分析与匹配应用研究[J].计算机工程与应用,2012,48(2):43-47.
[25]JWPL(Java Wikipedia Library)API工具包[EB/OL].[2016-06-09].https://dkpro.github.io/dkpro-jwpl/.
[26]廖福燕.本体构建中概念和关系获取方法研究[D].西安:西安建筑科技大学,2011.
[27]DAMERON O,et al.Measuring the evolution of ontology complexity:the gene ontology case study[J].PLo S One,2013,8(10):e75993.
[2]KUCUK D,ARSLAN Y.Semi-automatic construction of a domain ontology for wind energy using Wikipedia articles[J].Renewable Energy,2014,62:484-489.
[3]汤青,等.领域本体术语抽取研究[J].现代图书情报技术,2014(1):43-50.
[4]郭敏.基于谱聚类的复杂网络社团结构发现算法[D].西安:西安电子科技大学,2014.
[5]陈可佳.社会网络分析中的机器学习技术综述[J].南京邮电大学学报,2011,31(3):83-89,93.
[6]邵云飞,欧阳青燕,孙雷.社会网络分析方法及其在创新研究中的运用[J].管理学报,2009,6(9):1188-1203.
[7]袁园,孙霄凌,朱庆华.微博用户关注兴趣的社会网络分析[J].现代图书情报技术,2016(2):68-75.
[8]易明,王学东,邓卫华.基于社会网络分析的社会化标签网络分析与个性化信息服务研究[J].中国图书馆学报,2010,36(2):107-114.
[9]徐媛媛,朱庆华.社会网络分析法在引文分析中的实证研究[J].情报理论与实践,2008(2):184-188.
[10]邱均平,王菲菲.基于SNA的国内竞争情报领域作者合作关系研究[J].图书馆论坛,2010(12):34-40.
[11]邢杰,等.基于关键词网络分析的数字图书馆研究现状探讨[J].图书馆工作与研究,2011(8):35-38.
[12]陈云伟,方曙.社会网络分析方法在专利分析中的应用研究进展[J].图书情报工作,2014,56(4):90-95.
[13]周姗姗.基于Folksonomy模式的数字资源多维度聚合研究[D].长春:吉林大学,2014.
[14]NCI Thesaurus[EB/OL].[2016-06-09].http://ncit.nci.nih.gov/.
[15]The Gene Ontology[EB/OL].[2016-06-09].http://www.geneontology.org/.
[16]CORONNELLO C,et al.Gene-based and semantic structure of the gene ontology as a complex network[J].Physica A:Statistical Mechanics and its Applications,2016,485(15):313-328.
[17]杨哲.基于复杂网络的本体结构复杂性分析[J].计算机工程与应用,2007,36:77-79,116.
[18]张大陆,等.基于复杂网络的本体结构分析[J].同济大学学报,2009(2):258-261.
[19]CORRE P,et al.A multi-ontology approach to annotate scientific documents based on a modularization technique[J].Journal of Biomedical Informatics,2015,58:208-219.
[20]SASSON E,et al.Improving similarity measures of relatedness proximity:toward augmented concept maps[J].Journal of Informetrics,2015,9(3):618-628.
[21]杨健.基于No SQL的本体存储与查询研究[D].重庆:重庆大学,2015.
[22]DAVOODI E,et al.A semantic social network-based expert recommender system[J].Applied Intelligence,2013,39(1):1-13.
[23]YOO D,et al.An ontology-based co-creation enhancing system for idea recommendation in an online community[J].Data Base for Advances in Information Systems,2015,46(3):9-22.
[24]梁帅,等.本体结构特征分析与匹配应用研究[J].计算机工程与应用,2012,48(2):43-47.
[25]JWPL(Java Wikipedia Library)API工具包[EB/OL].[2016-06-09].https://dkpro.github.io/dkpro-jwpl/.
[26]廖福燕.本体构建中概念和关系获取方法研究[D].西安:西安建筑科技大学,2011.
[27]DAMERON O,et al.Measuring the evolution of ontology complexity:the gene ontology case study[J].PLo S One,2013,8(10):e75993.
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