基于知识图谱的网络舆情知识组织方法研究
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摘要
[目的/意义]大数据时代网络舆情呈现出新的特点,传统的舆情信息管理方法已经远远不能满足现实需求,必须开拓思路研究更为科学的网络舆情知识组织方法。[方法/过程]在分析网络舆情信息组织技术基础上,给出网络舆情知识图谱的结构化定义,分析网络舆情管理活动的知识需求,阐述网络舆情知识图谱的构建方法,提出了基于知识图谱的网络舆情知识组织架构。[结果/结论]实证研究表明,提出的方法可以提供更为精确化的管理能力,从而能够高效地发现舆情热点事件,为网络舆情的引导提供决策支持。
[Purpose/significance] In the new era,the network public opinion presents new characteristics. The traditional public opinion information management method has been far from meeting the actual needs. Therefore,it is necessary to develop a more scientific method to study the knowledge organizing of network public opinion. [Method/process] Based on the analysis of network public opinion information organizing technology,this paper defines the network public opinion knowledge map structuralization,analyzes the knowledge demand of network public opinion management activities,elaborates the construction method of network public opinion knowledge map,and proposes a knowledge organizing structure for network public opinion based on knowledge map. [Result/conclusion] The experiment shows that the proposed method can provide more precise management capabilities,so that it can efficiently detect public hotspots and offer decision support for network public opinion guidance.
[Purpose/significance] In the new era,the network public opinion presents new characteristics. The traditional public opinion information management method has been far from meeting the actual needs. Therefore,it is necessary to develop a more scientific method to study the knowledge organizing of network public opinion. [Method/process] Based on the analysis of network public opinion information organizing technology,this paper defines the network public opinion knowledge map structuralization,analyzes the knowledge demand of network public opinion management activities,elaborates the construction method of network public opinion knowledge map,and proposes a knowledge organizing structure for network public opinion based on knowledge map. [Result/conclusion] The experiment shows that the proposed method can provide more precise management capabilities,so that it can efficiently detect public hotspots and offer decision support for network public opinion guidance.
引文
[1]王静婷,徐震.一种基于知识技术的网络舆情内容分析系统框架[J].图书情报导刊,2016,1(2):139-143.
[2]谢明亮.基于知识管理的舆情机构库研究[J].江苏第二师范学院学报,2016,32(3):110-114,124.
[3]郭韧,陈福集.政府面向网络舆情的知识源整合研究[J].情报科学,2016,34(8):133-137,142.
[4]毛秀梅,杨晔.面向政府的网络舆情知识服务体系构建研究[J].情报科学,2016,34(9):124-128.
[5]周敬,陈福集.面向网络舆情的政府知识模型及知识管理应用研究[J].情报科学,2016,34(10):82-87.
[6]谷歌知识图谱[EB/OL].[2017-08-06]. http://www. google. com/insidesearch/features/search/knowledge. html.
[7]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.
[8]漆桂林,高桓,吴天星.知识图谱研究进展[J].情报工程,2017,3(1):4-25.
[9]徐增林,盛泳潘,贺丽荣,等.知识图谱技术综述[J].电子科技大学学报,2016,45(4):589-606.
[10] NOY N F,MCGUINESS D L. A guide to creating your first ontology[EB/OL].[2014-06-20]. http://protege. stanford.edu/publications/ontology_development/ontology101. pdf.
[11]中国人民解放军军事科学院.军事信息资源分类法:第2部分分类表:GJB 5402A. 2—2015[S].北京:总装备部军标出版发行部,2015.
[12]杨丽英,雷勇.面向信息处理的突发事件语料库分类体系研究[J].网络安全技术与应用,2012,21(3):29-31.
[13]万国,张桂平,白宇,等.基于特征加权的新闻主题句抽取[J].中文信息学报,2017,31(5):120-126.
[2]谢明亮.基于知识管理的舆情机构库研究[J].江苏第二师范学院学报,2016,32(3):110-114,124.
[3]郭韧,陈福集.政府面向网络舆情的知识源整合研究[J].情报科学,2016,34(8):133-137,142.
[4]毛秀梅,杨晔.面向政府的网络舆情知识服务体系构建研究[J].情报科学,2016,34(9):124-128.
[5]周敬,陈福集.面向网络舆情的政府知识模型及知识管理应用研究[J].情报科学,2016,34(10):82-87.
[6]谷歌知识图谱[EB/OL].[2017-08-06]. http://www. google. com/insidesearch/features/search/knowledge. html.
[7]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.
[8]漆桂林,高桓,吴天星.知识图谱研究进展[J].情报工程,2017,3(1):4-25.
[9]徐增林,盛泳潘,贺丽荣,等.知识图谱技术综述[J].电子科技大学学报,2016,45(4):589-606.
[10] NOY N F,MCGUINESS D L. A guide to creating your first ontology[EB/OL].[2014-06-20]. http://protege. stanford.edu/publications/ontology_development/ontology101. pdf.
[11]中国人民解放军军事科学院.军事信息资源分类法:第2部分分类表:GJB 5402A. 2—2015[S].北京:总装备部军标出版发行部,2015.
[12]杨丽英,雷勇.面向信息处理的突发事件语料库分类体系研究[J].网络安全技术与应用,2012,21(3):29-31.
[13]万国,张桂平,白宇,等.基于特征加权的新闻主题句抽取[J].中文信息学报,2017,31(5):120-126.