基于多源数据融合的科技决策需求主题识别研究
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摘要
大数据环境下,单一数据对科技决策支持的服务不充分、不全面,传统科技决策需求的获取方式较为被动,面对情报用户的决策需求愈加复杂的状况,增加了对用户情报需求描述、情报需求解读与情报服务的难度。为协同利用多源数据,使不同来源的信息相互补充,主动探测情报用户需求,提出一种基于多源数据融合的科技决策需求主题识别方法,以我国科技部机构用户需求主题识别为例,综合多源文本数据结合主题强度分析确定科技部机构用户的重点关注领域主题,确立主题属性,对需求主题在各个主题属性文本中进行词向量计算,从而主动识别出细粒度更高的机构用户科技决策需求主题。通过以科技部机构用户需求主题识别为例,融合多源数据相互补充印证,实现了主动捕获与探测用户的情报需求,从而对用户需求的掌握更加客观、合理、有效,丰富了情报服务的模式,为情报服务变被动为主动提供新理念、新方法。
In the big data environment,single-source data are not sufficient and comprehensive in the service of scientific and technical(S&T) decision-making support,and the access ways of traditional S&T demand are rather passive.The situation in which decision-making demand of information user is becoming increasingly complicated has increased the difficulty of user's information demand description,illustration,and intelligence service.In order to synergistically utilize multi-source data,so that information from different sources can complement each other,and to actively detect the demand of information user,this paper proposes a topic identification method of S&T decision-making demands based on multi-source data fusion.Taking the topic identification of Ministry of Science and Technology(MOST) institutional users' demands as an example,the paper synthesizes multi-source text data and combines topic intensity to analyze and determine the topics of their concerned areas,establish the topic attributes,and perform word vector calculation on demand topics in the texts of each topic,thus proactively identifying the fine-grained topics.Through the topic detection of MOST users' demands and the complementation and verification of multi-source data fusion,the paper achieves the active capture and detection of users' intelligence demands,so as to grasp the demands of users more objectively,reasonably,and effectively,enrich the modes of intelligence services,and provide new ideas and methods to the transformation from passive intelligence services to positive intelligence services.
In the big data environment,single-source data are not sufficient and comprehensive in the service of scientific and technical(S&T) decision-making support,and the access ways of traditional S&T demand are rather passive.The situation in which decision-making demand of information user is becoming increasingly complicated has increased the difficulty of user's information demand description,illustration,and intelligence service.In order to synergistically utilize multi-source data,so that information from different sources can complement each other,and to actively detect the demand of information user,this paper proposes a topic identification method of S&T decision-making demands based on multi-source data fusion.Taking the topic identification of Ministry of Science and Technology(MOST) institutional users' demands as an example,the paper synthesizes multi-source text data and combines topic intensity to analyze and determine the topics of their concerned areas,establish the topic attributes,and perform word vector calculation on demand topics in the texts of each topic,thus proactively identifying the fine-grained topics.Through the topic detection of MOST users' demands and the complementation and verification of multi-source data fusion,the paper achieves the active capture and detection of users' intelligence demands,so as to grasp the demands of users more objectively,reasonably,and effectively,enrich the modes of intelligence services,and provide new ideas and methods to the transformation from passive intelligence services to positive intelligence services.
引文
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[15] 郑彦宁,刘志辉,赵筱媛,等.基于多源信息与多元方法的产业竞争情报分析范式[J].情报学报,2013(3):228-234.
[16] 刘自强,王效岳,白如江.多维度视角下学科主题演化可视化分析方法研究——以我国图书情报领域大数据研究为例[J].中国图书馆学报,2016(6):67-84.
[17] 李静,靳丽娟,赵素君.一种基于WordNet语义增强和多源数据主题贡献度分析的科学研究前沿探测方法[J/OL].情报理论与实践:1-11[2018-10-31].http://kns.cnki.net/kcms/detail/11.1762.G3.20180411.0948.002.html.
[18] 化柏林.科技信息大数据在情报研究服务中的应用[J].图书情报工作,2017(16):150-156.
[2] 董克,邱均平.论大数据环境对情报学发展的影响[J].情报学报,2017(9):886-893.
[3] 肖勇.论基于“三大研究范式”之上的当代中国情报学学科体系与学科群体系构建[J].情报学报,2017(9):894-907.
[4] 胡昌平.信息管理科学概论[M].北京:科学技术文献出版社,1995.
[5] 化柏林,李广建.大数据环境下的多源融合型竞争情报研究[J].情报理论与实践,2015(4):1-5.
[6] 徐峰,姚长青.新时期我国科技创新情报需求转变的分析与思考[J].情报工程,2016(3):8-13.
[7] 陈峰.分析高层领导讲话识别竞争情报需求的方法[J].情报理论与实践,2012(9):57-60.
[8] 郭路生,刘春年,李颖.大数据环境下应急情报需求开发工程化范式构建研究[J].情报杂志,2017(8):52-57.
[9] 徐绪堪,吴慧中,张吉成,等.基于多源数据融合的突发事件决策需求研究[J].情报理论与实践,2017(11):40-44.
[10] 陶秀杰,龚婷,吴志强.基于交互式情报用户需求深度挖掘的电网信息检索方法研究[J].图书情报知识,2014(4):57-62.
[11] 李广建,化柏林.大数据分析与情报分析关系辨析[J].中国图书馆学报,2014(5):14-22.
[12] JAGADISH H V.Big data challenges and opportunities in financial stability monitoring[J].Financial Stability Review,2016.
[13] 化柏林.多源信息融合方法研究[J].情报理论与实践,2013(11):16-19.
[14] 李广建,杨林.大数据视角下的情报研究与情报研究技术[J].图书与情报,2012(6):1-8.
[15] 郑彦宁,刘志辉,赵筱媛,等.基于多源信息与多元方法的产业竞争情报分析范式[J].情报学报,2013(3):228-234.
[16] 刘自强,王效岳,白如江.多维度视角下学科主题演化可视化分析方法研究——以我国图书情报领域大数据研究为例[J].中国图书馆学报,2016(6):67-84.
[17] 李静,靳丽娟,赵素君.一种基于WordNet语义增强和多源数据主题贡献度分析的科学研究前沿探测方法[J/OL].情报理论与实践:1-11[2018-10-31].http://kns.cnki.net/kcms/detail/11.1762.G3.20180411.0948.002.html.
[18] 化柏林.科技信息大数据在情报研究服务中的应用[J].图书情报工作,2017(16):150-156.