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Data Analysis and Knowledge Discovery  2019, Vol. 3 Issue (10): 12-18    DOI: 10.11925/infotech.2096-3467.2019.0055
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Extracting Sentences of Research Originality from Full Text Academic Articles
Chengzhi Zhang1,3(),Zheng Li2,3
1School of Economics & Management, Nanjing University of Science & Technology, Nanjing 210094, China
2School of Information Management, Nanjing University, Nanjing 210023, China
3Jiangsu Key Laboratory of Data Engineering and Knowledge Service, Nanjing 210023, China
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Abstract  

[Objective] This paper analyzes full texts of academic articles, aiming to extract sentences of research originality as well as, exploring their characteristics. [Methods] We used full-text journal papers in the field of library, information and archives as experiment data. Then, we chose mark words, created extraction rules for sentences of research originality. Finally, we analyzed distribution of these sentences with the mark words, types, and locations. [Results] The extracted sentences were mainly divided into six categories, and most of them appeared in the top 24.8% section of each article. [Limitations] The proposed sentence extraction method needs to be optimized. [Conclusions] Sentences of research originality in the field of library, information and archives focus on concepts and theories. The categories and distributions of these sentences are various among different journals.

Key wordsSentences of Originality Research Evaluation      Information Extraction      Academic Evaluation      Full Text Analysis of Academic Articles     
Received: 14 January 2019      Published: 25 November 2019
ZTFLH:  TP391 G35  
Corresponding Authors: Chengzhi Zhang     E-mail: zhangcz@njust.edu.cn

Cite this article:

Chengzhi Zhang,Zheng Li. Extracting Sentences of Research Originality from Full Text Academic Articles. Data Analysis and Knowledge Discovery, 2019, 3(10): 12-18.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2019.0055     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2019/V3/I10/12

抽取对象 含义
命名实体识别 从众多信息中识别所需要的命名实体, 是信息抽取中最基本的任务
多语言实体识别 是在命名实体识别基础上的延伸, 可扩展至多种语言
模板元素抽取 将实体与其属性一同抽取出来, 形成实体对象
参照信息抽取 实现将不同地方的统一实体进行连接
模板关系抽取 进一步完善模板元素抽取, 补充各元素之间的关系
情节模板信息抽取 将时间、组织、人物或其他实体连接起来, 形成完整的事件
期刊名称 总数(篇)
大学图书馆学报 259
档案学通讯 360
档案学研究 461
国家图书馆学刊 18
情报科学 948
情报理论与实践 1 182
情报杂志 1 244
情报资料工作 105
图书馆 973
图书馆工作与研究 1 262
图书馆建设 843
图书馆论坛 948
图书馆学研究 1 626
图书馆杂志 805
图书情报工作 2 266
图书情报知识 345
图书与情报 527
现代图书情报技术 459
中国图书馆学报 298
合计 14 929
机构 评价句 出处 引用文献
北京大学 QuEChERS方法是一种快速便捷的前处理
方法, 由Anastassiades等在2003年首次
提出该方法由提取和净化两个主要步骤组
成, 主要用于果蔬中农药的检测。
木合他拜尔, 严华, 徐姗, 冯楠,
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南银. 色谱, 2015, 33(11): 1199-1204.
Anastassiades M, Lehotay S J, Stajinbaher D, et al. J. AOAC Int, 2003, 86(2): 412.
北京工业
大学
东南大学的郝英立等人最先在2005年指
出在结霜临界状态时冰粒的大小及其在冷
表面上的分布具有分形特征。
刘耀民, 刘中良, 黄玲艳, 孙
俊芳. 中国科学: 技术科学,
2009, 3911: 1864-1869.
Hao Y L, Jose I, Yong X T. Experimental study of initial state of frost formation on flat surface. J Southeast Uni, 2005, 35(1): 149-153
华东理工
大学
另外, Shi课题组于2009年第一次成功实
现了NiCl2(PCy3)2催化下芳基氰化物与反
应性较差的芳基硼酸酯或烯基硼酸酯的
Suzuki-Miyaura偶联反应。
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1407-1422.
Yu D G, Yu M, Guan B T, Li B J, Zheng Y, Wu Z H, Shi Z. Carbon-carbon formation via Ni-catalyzed Suzuki-Miyaura coupling through C-CN bond cleavage of aryl nitrile[J]. J. Org. Lett. 2009, 11(48): 3374-3377.
标志词 频次(比率) 例句
首次······提出 588(17.4%) “被引速度作为有效的文献计量学工具由A. Schubert等人于1986年首次提出”
最早······提出 485(14.4%) “协同概念最早是由德国物理学家赫尔曼·哈肯提出并形成系统性理论”
开创 163(4.8%) “香农(Shannon)从通信角度引入熵的概念开创了信息度量先河掀起了信息度量研究序幕”
早在······提出 125(3.7%) “T. Berners-Lee早在2006年便提出了关联数据的概念”
创始人 117(3.5%) “斯科特(Peter J. Scott)因此成为公认的文件系列系统创始人和文件连续体理论的先驱”
首先······提出 113(3.3%) “信息素养首先于1974年由美国信息产业协会主席PaulZurkow Ski提出”
始于 100(3.0%) “国外的政府信息资源规划研究始于20世纪80年代早期的马钱德、霍顿的信息资源管理阶段性理论”
源于 87(2.6%) “社会分类概念源于Barth”
追溯到 87(2.6%) “消费者决策过程研究最早可追溯到1967年P.Kotler提出的消费者购买决策黑箱理论”
最早······研究 61(1.8%) “最早对作者文献耦合方法进行实证研究的是Zhao Dangzhi”
标志词 频次(比率) 例句
源于 3 965(24.1%) “碎片化信息大多源于微媒体”
第一个 1 210(7.4%) “选择关键词构建共词矩阵是共词分析中的第一个关键步骤”
始于 1 081(6.6%) “佛山市智能图书馆建设始于2011年”
开创 816(5.0%) “移动电子商务开创了产品与服务新的模式”
追溯到 297(1.8%) “修谱者往往愿意将自己的祖先追溯到某个名人”
最早······出现 225(1.4%) “Twitter作为最早出现的微博, 发展相对成熟, 是学术界微博研究者的主要研究对象”
首创 214(1.3%) “统计表明,美国的技术创新有78%为其首创”
首先······分析 213(1.3%) “本研究首先对三种活动类型的特征进行调查分析, 包括普及性和价值性两个方面”
创始人 202(1.2%) “Twitter创始人之一埃文·威廉姆斯曾表示, 微博的真正价值不是粉丝数而是转发量”
首次······出现 112(0.7%) “重要的内容首次出现的位置通常在标题中”
评价句类型 分类依据 例句
概念理论类 由科研人员命名或定义某个概念或理论 “价值链由Michael E.Porter教授于1985年在其著作《竞争优势》一书中首次提出”
观点发现类 学者通过理论或实践研究提出的想法或发现, 且普遍具有一定长度 “引文分析法也存在缺陷, 早在1987年, King J就曾撰文指出同被引法的不足”
模型方法类 在研究过程中使用的方法 “TAM模型最早是由Davis在理性行为理论(Theory of Reasoned Action, TRA)的基础上提出”
派别领域类 开创了某个学派或是最先在某个领域进行研究 “《文献计量学》一书奠定了邱均平教授作为国内文献计量学奠基人之一的学术地位”
系统软件类 研究成果为开发的系统或者软件 “汉构是国际上最早基于HPSG理论、面向深层语言处理的中型汉语语法系统之一”
实践应用类 需要通过动手实践得到 “曼彻斯特大学的教授们首次提取出石墨烯···”
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