共查询到20条相似文献，搜索用时 46 毫秒
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[目的/意义]研究前沿的准确判断是国家宏观层面的战略需求,文献计量学作为一种定量研究方法广泛应用于科学主题探测和研究前沿识别中。[方法/过程]梳理研究前沿主题探测的发展历程和方法模型,引入全域微观模型的概念,详细介绍SciVal模块采用的主题创建方法,包括直接引用文献聚类、关键词主题命名和研究前沿遴选的主题显著性算法,并对SciVal创建的9.6万个主题和遴选出的前1%的研究前沿主题的特征进行实证分析。[结果/结论]全域微观模型可以同时一次识别整个科学领域的所有主题,但不同学科在研究前沿上表现存在差异,不能把主题显著性简单等同为重要性;主题论文数量与主题排名之间存在中度相关性;自动抽取的关键词术语从学科领域层和独特性上命名和描述主题;石墨烯相关前沿主题的演变趋势分析可以用于发现关键节点和新兴主题。 相似文献
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[目的/意义] 根据基金项目数据的特点,提出基于基金项目数据的研究前沿主题探测方法,以期识别出前瞻价值更高的研究前沿,为研究前沿识别相关研究提供借鉴思路。[方法/过程] 首先,基于PLDA模型识别蕴含在基金项目文本中的研究主题;然后基于主题-文档矩阵建立主题和基金项目文档的映射关系,在此基础上,利用主题的资助时间、资助金额和中心性指标进行研究前沿主题探测,从而识别出值得关注的研究前沿主题;最后,利用主题演化可视化分析方法,对研究前沿主题进行演化分析,以预测其发展趋势。[结果/结论] 研究结果表明,该方法可以根据基金项目数据的特点识别出蕴含在其中的研究前沿主题,并且能够分析研究前沿主题的分裂、融合等演化过程。 相似文献
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《Journal of Informetrics》2022,16(4):101343
In this study, MatrixSim, a new method for detecting the evolution paths of research topics based on matrix similarity, was proposed. In the analysis of research topic evolution with the help of co-word networks, in contrast to traditional methods of topic evolution path detection, such as cosine similarity and edge similarity, MatrixSim is based on the local community structure of topic communities in co-word networks and considers the similarity of research topics in both nodes and edges, that is, words and inter-word relations. Using the library and information science field as an example, two sets of experiments were designed for topic similarity detection and subject-specific research topic evolution analysis to evaluate and verify the performance of MatrixSim in detecting the evolution paths of research topics and its validity and feasibility in research topic evolution analysis. The results confirm that MatrixSim performs well in detecting the evolution paths of research topics. It can correlate important research topics, help describe the research development process in scientific fields, reveal the internal evolutionary features of research topics, and thus discover and track the research frontiers in scientific fields. This study provides significant methodological support for researchers conducting prospective research activities. 相似文献
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[目的/意义]运用深度学习技术,提出结合时间和空间特征的测度(速度、覆盖度和迂回度)方法,用于量化学者研究主题演化,从而为基于内容的学者评价提供量化依据。[方法/过程]提出三维指标框架,其中速度反映作者改变研究主题快慢的平均程度,覆盖度反映作者研究内容所覆盖的主题广度,迂回度反映作者研究路径的曲折性。使用微软学术数据集中计算机科学的作者进行实证研究,并考察学者研究主题演化的三维测度和学者学术影响力和生产力的关系。[结果/结论] 实证研究结果显示,覆盖度与总被引量和总发文量的关系为单调递减,这一特征说明聚焦于特定研究主题较为深入的作者,其发文量和影响力都较大。作者研究主题演化的"速度"和"迂回度"与总被引量、总发文量都存在先增加后减少的倒U型关系。所提出的多维度指标框架不仅可在理论上丰富科学计量学对于学者研究主题转移演化及其机制的理解,而且结合深度学习模型提出了问题的解决思路。 相似文献
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[目的/意义]旨在深入语义层面对研究主题进行分析。[方法/过程]提出基于本体的研究主题语义分析方法,从语义类型和与语义关联两个维度展开,并在实证研究过程中,以“医学信息学”为例,对方法进行验证。[结果/结论]结果表明,语义类型分析能够辅助研究者对研究主题的内容进行进一步的语义理解;语义关联分析从语义角度分析各个研究主题在语义含义上的关联,在辅助研究者分析某领域研究主题时,能够综合分析相关主题,并发现新的研究交叉点。 相似文献
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文章目的在于梳理30多年来健康素。养领域研究的演进路径,拇示、研究热点与研究前沿。为此,将1990--2010年SCI、SSCI数据库中收录的主题为“健康素养”的论文数据作为研究对象,应用Citespace知识可视化软件绘制文献共被引网络闺谱,析出健康素养演进过程中：的关键节点文献;并应用其文献共引一名词短语混合网络图谱、关键词聚类和膨胀词探测4功能分析了研究热点与研究前沿。11篇关键节点文献很好地展示了健康素养领域研虎的演进路径2个明显的聚类以及19个突观词表征了研究热点与研究前沿。文章认为健康素养和精神健康素养是目前两个主流研凳领域矗健康素养内涵、健康材料的可读性、快速潮评工具和方法、健康教育、突发性事件以及以艾滋病为代表盼慢性痛与传染病是健康素养的研究前沿与发展趋势。 相似文献
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科学前沿迁移规律研究是科学计量学研究的热点主题,能够体现不同时期科学家关注点以及科学研究侧重点的动态变化。基于引文、主题词、网络和离群数据的科学前沿迁移研究方法和数据分析、引文分析、时序分析和网络分析四类科学前沿迁移研究工具,比较时间线可视化、科学地图可视化、Histcite引文编年可视化、知识领域可视化和VxInsight可视化技术,阐明科学前沿迁移研究的可视化、载体迁移、低频现现象等发展趋势。 相似文献
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国外消费者健康信息学研究综述 总被引：2，自引：1，他引：1
[目的/意义]分析消费者健康信息学从诞生至今20多年的发展状况,并在文献评述基础上提出建议,为国内消费者健康信息学研究提供参考。[方法/过程]对近年来国外有关消费者健康信息学文献进行梳理,主要对来自Web of Science、Science Direct、Scopus、PubMed 4个数据库中相关主题的研究性论文、综述性论文及会议论文进行调研和分析。[结果/结论]虽然有关消费者健康信息学的研究成果硕果累累,但是目前对消费者健康信息学的定义尚未统一。未来对消费者健康信息学定义需要达成共识,同时数字健康鸿沟也是该领域研究的重点。 相似文献
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[目的/意义] 揭示2009年以来国际图书情报领域研究前沿的主题结构及其演化规律,探测未来研究的前沿趋势,为相关研究者追踪前沿信息提供参考。[方法/过程] 以Web of Science为数据源,以2009-2016年5月发表在图书情报领域12种核心期刊的文献为研究对象,基于文献共被引分析方法,利用CiteSpaceⅢ软件工具,绘制2009-2016年5月国际图书情报领域研究前沿主题的知识图谱。[结果/结论] 2009年以来,国际图书情报领域形成了h指数、特征因子、文献计量知识图谱、科研绩效等十二大研究主题。其中,通过转折节点文献,派生出新的研究前沿,形成了h指数、语言模型、概念模型、科研绩效、替代计量学、信息情感等前沿主题,未来研究呈现多元化的发展趋势。 相似文献
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��[Purpose/significance] This paper proposes the identification of the core research topics and their evolution path visualization methods, in order to provide reference for the field subject evolution analysis research, which has certain significance for revealing the evolution characteristics and development laws of the core topics.[Method/process] Using the LDA model for topic recognition and combining multi-dimensional scaling analysis and visualization techniques to map LDA topic recognition results to two-dimensional space. The topic similarity algorithm was used to detect the association between adjacent time topics, a new visual display method was proposed. We constructed cross-evolution paths of different types of research topics to reveal the dynamic changes of core topics and secondary topics in the evolution process.[Result/conclusion] Taking the medical health information field in China as an example, the research results show that the core research topics in the field of medical and health information in China mainly include electronic health records and Internet medical treatment. Among them, core themes such as health management and smart medical treatment show a good development trend. 相似文献
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[目的/意义]主题演化对科技前沿探测、创新战略部署具有十分重要的作用。[方法/过程]将主题演化分析过程分解为主题的表示、相似性关联和强度演化计算几个步骤,提出一种主题强度演化与预测模型,使用LDA模型进行主题的表示,提出内容、共现和趋势相似度等维度进行主题关联计算,引入基于Prophet的预测-修正模型进行主题演化趋势预测。并以干细胞领域为例,进行演化的实证分析。[结果/结论]实验表明,对每个研究主题采用Logistic增长模型进行预测R2Score都达到0.90以上,表明Prophet的Logistic增长模型与该领域主题增长趋势规律相符合,能够较好地拟合主题强度的演化趋势。提出的主题演化模型对专业领域内主题分布与演化分析有一定的借鉴意义。 相似文献
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The adoption of e-governing practices has revolutionised the administrative machinery of governments worldwide by improving efficiency, transparency, and accountability. Researchers and administrators often aim to identify emerging research fronts and the timeline of the evolution to forecast and implement technology. In this work, we systematically investigate the trajectory of the global evolution and emerging research fronts as well as the prospects for e-governance using citation network analysis. The growth curve fitted to the number of articles published per year shows that the research activities are still in the ascendant phase. We visualise the global main path of the citation network and investigate the patterns to trace the knowledge diffusion path, major milestones, and emerging research fronts. The cluster analysis identifies the major topics of research as administration and information system management, e-governance framework design, efficiency or quality evaluation, and the application of social networks and open data leading to e-democracy. The adoption of open data and social networking for user interactions with government that leads to participatory governance are the emerging research trends. We also identify research that can have a future impact based on network parameters. The results contribute to the literature by setting the focus of future research, and assisting administrators in selecting suitable models and methodologies, and manufacturers with the development of required technical devices suitable for the upcoming phase of symbiosis. 相似文献
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[目的/意义]分析中国国内基于主题模型的科技文献主题发现及演化研究进展,以期为相关研究人员提供参考借鉴及研究思路。[方法/过程]选取中国知网(CNKI)数据库及万方数据知识服务平台作为文献来源,检索并筛选相关文献,通过人工判读提炼出基于主题模型的科技文献主题发现及演化研究的分析流程,并采用文献分析法对流程中国内研究人员所使用到的策略、方法、分析手段等进行归纳和总结。[结果/结论]研究已初具规模,形成较为完整的分析流程,同时各个流程环节上所涉及到的策略、方法和分析手段较为多样化。另外,也存在着一些问题:主题模型方法在科技文献领域的应用尚且不成熟,主题数目固定,缺少对主题模型应用效果的评价方法与准则。 相似文献
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Samar Binkheder Raniah Aldekhyyel Jwaher Almulhem 《Journal of the Medical Library Association》2021,109(2):219
Objective:Understanding health informatics (HI) publication trends in Saudi Arabia may serve as a framework for future research efforts and contribute toward meeting national “e-Health” goals. The authors’ intention was to understand the state of the HI field in Saudi Arabia by exploring publication trends and their alignment with national goals.Methods:A scoping review was performed to identify HI publications from Saudi Arabia in PubMed, Embase, and Web of Science. We analyzed publication trends based on topics, keywords, and how they align with the Ministry of Health''s (MOH''s) “digital health journey” framework.Results:The total number of publications included was 242. We found 1 (0.4%) publication in 1995–1999, 11 (4.5%) publications in 2000–2009, and 230 (95.0%) publications in 2010–2019. We categorized publications into 3 main HI fields and 4 subfields: 73.1% (n=177) of publications were in clinical informatics (85.1%, n=151 medical informatics; 5.6%, n=10 pharmacy informatics; 6.8%, n=12 nursing informatics; 2.3%, n=4 dental informatics); 22.3% (n=54) were in consumer health informatics; and 4.5% (n=11) were in public health informatics. The most common keyword was “medical informatics” (21.5%, n=52). MOH framework–based analysis showed that most publications were categorized as “digitally enabled care” and “digital health foundations.”Conclusions:The years of 2000–2009 may be seen as an infancy stage of the HI field in Saudi Arabia. Exploring how the Saudi Arabian MOH''s e-Health initiatives may influence research is valuable for advancing the field. Data exchange and interoperability, artificial intelligence, and intelligent health enterprises might be future research directions in Saudi Arabia. 相似文献
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[目的/意义] 基于主题关联相似度揭示主题汇聚及变异过程,识别学科交叉主题及交叉模式,归纳学科主题的演化趋势及演化路径模式。[方法/过程] 获取情报学学科科研论文的高频主题词,构造主题词共词矩阵,利用网络社区演化分析工具生成学科主题演化网络图,结合指标数据对学科主题演化过程进行分析。[结果/结论] 总体上看,情报学学科的研究主题虽然在反复地变化,但核心主题一直存在;扩张、收缩和合并是研究主题最普遍的变化态势,分裂现象较少,产生和消亡现象存在;有3条特定社区演化轨迹清晰地贯穿始终,活跃度相对稳定,反映了3类核心研究主题;3类核心研究主题的演化路径呈现出升华吸纳、共融迭新和辐射推进3种演化模式。研究结果显示,基于主题关联学科主题演化路径的多模式识别方法既能从宏观层面呈现学科主题演化形式,也能从微观层面分析学科主题交叉模式,结合二者可揭示学科主题的继承或创新,预测学科交叉主题的发展方向。 相似文献
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时间线和地形式可视化图谱:科学传播研究前沿演进趋势分析 总被引：1，自引：0，他引：1
研究前沿是在一门学科领域中研究者最热衷、最新的研究主题.运用时间线和地形式可视化图谱方法进行研究前沿的确定和描绘,由原来的二维时间线图谱扩展至三维动态地形式图谱,为研究前沿的发展趋势绘制更加清晰可视化并具有动态性的知识图谱.以一份科学传播研究领域的权威期刊<科学传播>(Science Communication)杂志1994～2007年的数据为例,对科学传播的研究前沿进行了可视化地梳理和描述,绘制出时间线和地形式可视化图谱,试图随着时间变化来演示科学传播领域研究前沿的动态变化过程与发展趋势,为技术预测和学科发展提供借鉴. 相似文献
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[目的/意义]随着信息资源在数量和种类上的急剧增长,学科间的交叉融合不断涌现,快速主动地从海量信息资源中识别和判断研究主题的发展演化是实现科技创新的基础。[方法/过程]在相关理论调研的基础上,结合医学领域的资源特点,提出一种基于LDA模型的主题演化探测模型和相应的流程步骤。主要步骤包括医学主题词抽取、主题识别、主题关联、关键主题识别、关键主题的演化主路径识别、演化主路径上主题分裂、融合事件识别,实现深度、细致的主题演化分析。[结果/结论]选用乳腺癌治疗研究文献为实验案例,对判断模型进行试验并对结果进行分析验证,证实提出的技术方法具有一定的可靠性。 相似文献
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BACKGROUND: Doctors need information skills to deliver health care in the 21st century. There is concern that those who trained before the 'information age' will be inadequately equipped for their work. OBJECTIVES: To assess doctors' use of computers for clinical tasks, and their knowledge and skills in health information management and technology. DESIGN: Questionnaire survey. SETTING: An acute NHS trust in the UK. PARTICIPANTS: 96 (83%) of all doctors in the trust responded. MAIN OUTCOME MEASURES: Proportion of respondents reporting the following: use of computer-based systems for clinical tasks, knowledge in eight health informatics topics, skills in using specific hardware and software applications. Also comparison of reported skills between senior and junior staff; proportion of doctors identifying specific training needs. RESULTS: All but one (1%) of the responding doctors used a computer regularly. Over three quarters of respondents reported they were semi-skilled or fully skilled in basic office applications, though the juniors scored significantly more highly than the seniors for some applications. However, 44% of doctors reported no skills in database software, identifying this as a training need. Around half of the doctors were unaware of health informatics topics, including electronic patient records, the Caldicott report and data protection law. In each case the senior doctors were significantly more aware than the juniors of the topic in question. CONCLUSION: Both junior and senior doctors have basic computer literacy, but nearly half of this population identify the use of database software as a training need. In addition, there are several health informatics topics of which a large proportion of doctors, particularly the juniors, have little knowledge, but which have not been identified as training needs. Some recommendations are made for provision of in-house health informatics education for doctors. 相似文献
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[目的/意义]基于大量专利文献数据的核心技术主题识别有助于识别某技术领域的关键技术、分析关键技术的发展方向,是进行技术创新的基础情报工作,对于研究人员、企业乃至国家层面都具有一定的意义。[方法/过程]提出基于Chunk-LDAvis的核心技术主题识别方法,首先基于经典LDA模型进行主题识别,然后利用名词组块对初始LDA主题识别结果进行标注,构建Chunk-LDA主题识别结果,提高其可解读性;然后基于社会网络分析方法构建主题网络,识别核心技术主题;基于R语言的LDAvis工具包绘制可交互的Chunk-LDAvis核心技术主题关联分析图谱,发现核心技术主题的隐含联系,辅助进行核心技术主题识别。[结果/结论]通过对纳米农业领域进行实证研究,验证了本文提出方法的准确性和可行性。 相似文献