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《Journal of Informetrics》2020,14(1):100999
The current study has two objectives. First, we explore the characteristics of biological entities, such as drugs, and their side effects using an author–entity pair bipartite network. Second, we use the constructed network to examine whether there are outstanding features of relations between drugs and side effects. We extracted drug and side effect names from 169,766 PubMed abstracts published between 2010 to 2014 and constructed author–entity pair bipartite networks after ambiguous author names were processed. We propose a new ranking algorithm that takes into consideration the characteristics of bipartite networks to identify top-ranked biological drug and side effect pairs. To investigate the relationship between a particular drug and a side effect, we compared the drug and side effect pairs obtained from the network containing both drug and side effect with those observed in SIDER, a human expert-curated database. The results of this study indicate that our approach was able to identify a wide range of patterns of drug–side effect relations from the perspective of authors’ research interests. Further, our approach also identified the unique characteristics of the relation of biomedical entities obtained using an author–entity pair bipartite network. 相似文献
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We propose a backward tracking model for measuring knowledge transfer in the whole translational research spectrum. Using the drugs-patents-papers-grants backward linkages, we try to figure out the funding-science-technology-innovation translational pattern and ponder some policy implications on e.g., which priority areas and knowledge convergence level are more likely to generate new drugs. The drug-patent linkage data was accessed through the USFDA Orange Book, covering a drug's active ingredient, formulation, or methods of use for approved indications. It will take about 10 years from the application of earliest patent to the approval of the new drug. Also such high-value patents in FDA Orange Book tend to cite scientific knowledge published on average 10–15 years ago. The technology linkage of new drugs was relatively stable while the science linkage of technology inventions increased rapidly. Among the scientific papers cited by drug patents, private-institution originated papers are only a quarter of the public. By linking theses scientific papers with funding sources, we found a large majority (90%) are public-funded and only a very small part are private-funded or public-private joint-funded. Our study also indicates the importance of research on such fields as pharmacology, chemistry (including medicinal chemistry, biochemistry, and organic chemistry), molecular biology, neurosciences, and immunology on new drugs innovation. There is no obvious relationship between “basicness” and linkages to the resulting patents’ impact and to drugs innovation. A balanced basic research and applied research maybe essential for fostering drug innovation because it is a complete chain translating from basic discovery to clinical evidence then to clinical practice. In order to achieve successful pharmaceutical innovation, rather than focusing on only technology, convergence with science at moderate levels (maybe 1/3) is suggested. 相似文献
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[目的/意义]复杂网络的社团结构研究已逐渐成为科学家借助文献数据开展科学结构研究的有力工具，社团划分效果的不同对科学结构的解读有着举足轻重的影响。本文对混合网络社团划分方法进行梳理，以期对该领域的相关研究提供借鉴参考。[方法/过程]通过文献调研，阐明混合网络的概念与类型，从网络构建或算法革新角度对各类型混合网络的社团划分研究进行概述，也对支撑混合网络社团划分的经典算法进行简介。[结果/结论]通过系统地梳理总结不同类型混合网络的社团划分工作，为后续的网络分析研究提供研究的视角和方法，同时揭示其在科学结构研究中所面临的挑战与所具有的现实意义，展望今后可能进一步拓展的相关研究方向。 相似文献
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基于社会网络分析的国内计量学作者合作关系研究 总被引：1，自引：0，他引：1
利用社会网络分析方法,研究我国计量学领域作者合作关系。选取2000-2010年论文数据,通过分析合著关系网络密度、中心性及小团体,得出计量学作者总体合作程度高,但核心作者间合作有待加强;刘则渊及邱均平为该领域中心作者;作者合作关系受地理位置影响大;该领域研究群体以图书情报、医学情报人员为主;各小团体均有其本身特点。通过本研究,以揭示该领域作者合作关系,促进知识交流及学科发展。 相似文献
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[目的/意义]社交媒体的出现为医疗健康数据的收集提供了新的途径,应用自然语言处理技术从社交媒体中抽取患者报告的ADR（Adverse Drug Reaction,药物不良反应）信号对于改善药物不良反应监测的临床和科学知识具有很大的潜力。然而,从社会媒体中提取患者报告的ADR信号仍然面临重大挑战。为此,开发一个利用高级自然语言处理技术从健康主题社交媒体中抽取ADR信号的研究模型。[方法/过程]该模型首先采用基于多词典源匹配的方法,从嘈杂的社交媒体中识别医学实体;然后采用最短依存路径核函数为基础的统计学习方法提取药物不良事件;并利用药品安全数据库的语义知识过滤药物的治疗和适用症信息以及否定的药物不良事件;最后,对报告源进行分类剔除传闻等噪音信息。[结果/结论]通过收集糖尿病论坛上的数据对模型的有效性进行验证,结果显示该模型的每一部分都有助于其整体性能的提升。 相似文献
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面向LOD的关联发现过程的定位、目标与复杂性分析 总被引：1，自引：1，他引：0
本文以关联数据应用过程中的关联发现过程为研究对象,分析了面向关联开放数据(LOD)的关联发现过程的定位、目标与复杂性。本文认为,关联发现过程处于关联数据应用过程三阶段(数据发布、数据互联与数据消费)中的第二阶段。关联发现过程的整体目标是构建多类资源之间的关联数据网络,该过程的本质就是关联数据网络不断演变的过程。关联发现的过程具有多任务、多路径、多步骤等复杂性特征。目前流行的关联发现框架还存在缺乏对整个网络演变过程的支持、任务类型单一、缺乏流水线机制等不足。因此,关联发现技术的研究急需新的面向整个关联数据网络的、支持完整演变过程的、支持多任务集成的理论、方法与框架。图5。表1。参考文献17。 相似文献
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[目的/意义]信息资源发现与传递服务一直是图书馆的核心业务,目前在欧美出现一种新形式即基于Bento模式的联邦检索服务系统,研究其最新发展趋势对完善我国图书馆发现系统有重要参考价值。[方法/过程]通过文献调查、比较研究、案例分析等方法,对比国内外发展现状,揭示混合排序的不足和Bento模式的优点,并以美国伊利诺大学香槟分校（UIUC）图书馆为例说明其应用和未来发展趋势。[结果/结论]实践证明Bento模式更有利于实现从全资源发现向全图书馆发现的转变,检索效果和图书资源利用率均有较大幅度的提升。 相似文献
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在不同领域,随着数据规模的日益扩大,对于数据的自动分析技术已变得不可或缺。人们通过数据挖掘技术可以更高效地得到大规模数据的各种特征。在知识发现的过程中,无论对于数据分析还是数据挖掘,可视化都是将数据中的特征转换为知识的关键步骤。文章将从可视化分析与信息可视化的角度概述在科技信息领域中关系数据的可视化分析方法及其应用。首先,文章介绍在科技信息领域可视化的相关方法,以及信息可视化的特点与局限;接着介绍可视化分析在科技信息领域的相关工具与系统;最后给出一个对我国生命科学领域论文同被引网络的可视化分析实例。通过对该同被引网络的可视化分析,可以很直观地发现在该研究领域的不同研究方向以及引领这些研究方向的主要论文及其关系。 相似文献
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通过对《书目记录的功能需求》（FRBR）概念模型体系结构中实体、属性及关系这3个基本要素的分析,探寻由FRBR模型抽取出的馆藏资源元数据关联网络的构成要素,并对符合FRBR的馆藏资源元数据知识节点与关联关系所构成的关联网络结构进行层次划分,形成以元数据记录属性为支撑的微观层面关联网络及以元数据记录之间或规范数据集之间关联关系作为支撑的宏观层面关联网络。而词汇集的建立、术语复用机制、数据集链接桥机制成为构建馆藏资源元数据关联网络的基本要素。馆藏资源元数据关联网络的建立对于揭示馆藏资源内部的知识结构、扩展知识检索的范围、推荐关联知识、辅助知识发现等均具有重要的价值。 相似文献
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为研究专利分析方法、技术以及应用等方面的最新进展,采用文献计量法,对以专利分析为主题的文献进行分析,总结国外专利分析主题的研究进展情况。利用汤森路透WOS(web of science)引文检索平台,检索 2000-2012年以"专利分析"为主题的文献,通过主题分析(高频关键词)以及关键词共现分析,得到国外专利分析相关文献的主题。研究发现,国外近10年以专利分析为主题的文献主要围绕专利计量法、专利语义分析、社会网络分析与模型、文本挖掘、可视化以及科学-技术关联等方面,并在此基础上展开了新的研究。 相似文献
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[目的/意义]分析并提出虚拟健康社区文本数据的知识发现策略,构建虚拟健康社区文本数据知识发现模型。[方法/过程]通过总结分析虚拟健康社区文本数据特点,针对其特点带来的数据挖掘困难制定相应的知识发现策略,并在DIKW体系指导下,依据提出的知识发现策略构建虚拟健康社区文本数据知识发现模型。通过应用计算机编码、自然语言处理技术、句法分析、制定推理规则等方法实现从自由文本数据到药物不良反应智慧的数据价值升华过程。[结果/结论]通过实证研究验证提出的知识发现策略和知识发现模型的有效性和可操作性,为后续虚拟健康社区文本数据知识发现的相关理论与实证研究提供参考。 相似文献
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基于超链分析的Web资源自动发现技术 总被引：2，自引：0，他引：2
传统的Web资源自动发现是基于Web页面内容实现的。本文试图从超链分析的角度探讨Web资源的自动发现技术。超链分析技术起源于社会网络分析和科学引文分析理论,它只分析页面之间的关系,而不关心页面本身的属性。通过试验证明,单纯使用超链,根据用户提供的网页实例,我们能够自动发现与学科资源相关的网站。该技术可以有效的减少网络爬行器的无谓爬行,提高采集效率,减轻网络负担,在学科资源建设中起了重要的作用。 相似文献
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《Journal of Informetrics》2014,8(1):197-211
Author co-citation analysis (ACA) has long been used as an effective method for identifying the intellectual structure of a research domain, but it relies on simple co-citation counting, which does not take the citation content into consideration. The present study proposes a new method for measuring the similarity between co-cited authors by considering author's citation content. We collected the full-text journal articles in the information science domain and extracted the citing sentences to calculate their similarity distances. We compared our method with traditional ACA and found out that our approach, while displaying a similar intellectual structure for the information science domain as the other baseline methods, also provides more details about the sub-disciplines in the domain than with traditional ACA. 相似文献
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《Communication monographs》2012,79(2):193-214
In recent decades a distinctive literature has accumulated discussing the role of gender, feminism, and women's studies‐related research (GFWS) in the communication field; however, questions have persisted about how this research is represented in the field's publications. Contributing to the literature on the sociology of the field's scholarship, the history of the GFWS literature was sketched in a field test of a concept mapping technique that tracks patterns of publication and isolates conceptual associations within the titles of GFWS articles. The data for the study were significant concepts extracted from titles of 31,500 articles appearing in 70 communication journals and annuals within the period 1970 to 1997. The study accomplished several goals. First, it examined the accuracy of historical arguments about GFWS scholarship, arguments that bear on the issue of fair treatment of GFWS scholarship within the field. Second, it examined GFWS articles by publication source to assess patterns of representation by journal. Third, it provided a response to requests by some scholars working in the area for a thorough survey of the dimensions of the GFWS literature. Findings support the idea that GFWS scholarship is represented by a unique constellation of conceptual relationships. Feminist scholarship is found to have a history unto itself separate from that of studies of gender or sex differences, and has entered the literature in two distinctive eras. As well, feminist research was found to have a unique and uneven pattern of representation in the field's literature. By identifying threads of theoretical connection between articles in a widely dispersed literature, the concept mapping methodology is argued to provide one means for offsetting the fragmentation of the discipline's scholarship that has occurred throughout the last three decades as a result of the rapid proliferation of new specialized communication journals. 相似文献
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《Medical reference services quarterly》2013,32(3):37-52
Health science library service often includes identifying drugs manufactured, prescribed, or dispensed in other countries. Discussion of complexities in drug nomenclature, establishing equivalency, and differing standards adopted by reference sources may encourage more effective information provision. Statistical data gathered from a drug information center's experience with identification requests can indicate relevant sources. An analysis of such data, collected over a 40-month time period and involving over 550 foreign drug information questions, may contribute practical knowledge to individuals responsible for collection development, reference service, or bibliographic instruction. Guidelines for print and online search strategies are included, applicable in answering both domestic and foreign drug information questions. 相似文献
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[目的/意义] 针对目前全领域科学知识图谱构建方法中存在的技术难点,结合网络嵌入模型、机器学习聚类、流形学习可视化算法等人工智能领域的方法与模型,提出一套全新发现科学结构的知识图谱构建方案,以完善科学结构发现与可视化布局,并拓展科学知识图谱的分析应用场景。[方法/过程] 引入基于深度学习的网络嵌入模型和聚类方法改进原有的网络社团划分聚类方法,利用流形学习降维可视化算法扩大数据处理能力,并设计由下至上分层可视化布局方法,提升可视化图谱的稳定性与细节揭示能力。[结果/结论] 以科睿唯安公司的基本科学指标数据库（ESI）研究前沿中高被引论文作为分析数据集,使用新聚类算法得到1 169个研究领域,通过改进的可视化布局算法形成全领域科学结构图谱。与前几期科学结构图谱相比,本文提出的方法支持更大规模的数据分析,对可视化细节揭示与稳定性也有大幅优化,可以更好地展示全领域科学研究宏观结构及内在关系,为全领域科学知识图谱的绘制与构建提供更可靠的方法和技术支持。 相似文献
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《Journal of Informetrics》2022,16(1):101242
Main path analysis (MPA) is the most widely accepted approach to tracing knowledge transfer in a research field. In this study, we extracted multiple longest paths from the multidisciplinary academic field's citation network and integrating topic modeling to the extracted paths. We consider three main aspects of trajectory analysis when analyzing the represented documents through the extracted paths: emergence, authority, and topic dynamics. For path extraction, we adopt the longest path algorithm that consists of the following three steps: 1) topological sort, 2) edge relaxation, and 3) multiple path extraction. For topic integration into multiple paths, we employ latent Dirichlet allocation (LDA) by utilizing the topic-document matrix that LDA derives to select an article's topic from the citation network, where each article is labeled with the topic that is assigned with the highest topical probability for that article. We conduct a series of experiments to examine the results on a dataset from the field of healthcare informatics that PubMed provides. 相似文献