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对Altmetrics的发展过程及现状进行了较为系统的总结,主要包括Altmetrics工具的起源、危机和转型三方面,厘清Altmetrics工具的产生背景,系统阐释了其面对来自科学共同体内、外的质疑和挑战,采取的积极应答、改进和发展的具体策略。 相似文献
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研究中文学术论文用户使用模式有助于分析使用规律,为应用决策提供依据。本文以八个学科被CSSCI或CSCD收录的61本开放获取期刊发表于2014—2015年的学术论文为样本,以期刊官网和信息集成平台上的使用数据为来源,采用Usage Metrics的方法,从用户平台偏好和用户兴趣偏好两方面比较中文学术论文的用户使用模式。研究发现:①期刊官网与信息集成平台的用户平台偏好存在差异。一是从学科视角看,用户整体上倾向于使用期刊官网而不是信息集成平台获取所需论文,而社会科学的信息集成平台篇均下载次数均大于自然科学。二是从期刊视角看,社会科学用户比自然科学用户更倾向于使用信息集成平台获取所需论文;与信息集成平台相比,期刊官网的用户下载数据呈现更为明显的“两级分化”现象;期刊官网下载次数与信息集成平台下载次数整体上的相关性较低。②期刊官网与信息集成平台的用户兴趣偏好存在差异。每本期刊官网和信息集成平台下载次数前20%的学术论文的Jaccard相似系数较低;在所列举的图书馆、情报与文献学中,期刊官网与信息集成平台的用户关注主题不同。图7。表5。参考文献37。 相似文献
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本文借鉴商业银行经济资本的管理思路,将地方政府的可偿债财政收入和可出售资产作为覆盖风险的“资本”。选取2014年12月31日合肥市18只未到期中期城投债为样本,基于CreditMetrics模型,利用银行间债券市场的国债利率和信用风险溢价调整远期贴现率,采用国内评级机构提供的信用风险转移矩阵计算单只城投债的VaR,引入Copula函数估计相关系数矩阵,并通过MonteCarlo模拟得到城投债组合的VaR,最后结合合肥市财政收入和政府资产的相关数据,确定合肥市地方债券的发行限额。 相似文献
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Miriam Madsen 《教育政策杂志》2021,36(1):64-83
ABSTRACT The increased use of quantitative education data is often regarded by scholars as evidence of the emergence of’governing by numbers’. These scholars ascribe major stakeholders such as the OECD and nation states agency as they produce, distribute and consume data, and respond to these with policy and management initiatives. This paper argues that metrics themselves have a configurative agency that affects education in terms of educational ideas and designs. The paper illustrates this point by analysing two cases of graduate employability metrics, each of which configures education differently, and discusses how the configurative agency of metrics can become the focal point of a different research agenda using distinct analytical concepts drawn from the sociology of quantification and new materialism. The paper concludes that such a research agenda can enable actors involved in the design and development of education to enter into a professional dialogue and engagement with education data, rather than merely dismissing it. 相似文献
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《Information processing & management》2023,60(5):103452
Word embeddings, which represent words as numerical vectors in a high-dimensional space, are contextualized by generating a unique vector representation for each sense of a word based on the surrounding words and sentence structure. They are typically generated using such deep learning models as BERT and trained on large amounts of text data and using self-supervised learning techniques. Resulting embeddings are highly effective at capturing the nuances of language, and have been shown to significantly improve the performance of numerous NLP tasks. Word embeddings represent textual records of human thinking, with all the mental relations that we utilize to produce the succession of sentences that make up texts and discourses. Consequently, the distributed representation of words within embeddings ought to capture the reasoning relations that hold texts together. This paper makes its contribution to the field by proposing a benchmark for the assessment of contextualized word embeddings that probes into their capability for true contextualization by inspecting how well they capture resemblance, contrariety, comparability, identity, relations in time and space, causation, analogy, and sense disambiguation. The proposed metrics adopt a triangulation approach, so they use (1) Hume’s reasoning relations, (2) standard analogy, and (3) sense disambiguation. The benchmark has been evaluated against 22 Arabic contextualized embeddings and has proven to be capable of quantifying their differential performance in terms of these reasoning relations. Results of evaluation of the target embeddings revealed that they do take context into account and that they do reasonably well in sense disambiguation but have weakness in their identification of converseness, synonymy, complementarity, and analogy. Results also show that size of an embedding has diminishing returns because the highly frequent language patterns swamp low frequency patterns. Furthermore, the suggest that future research endeavors should not be concerned with the quantity of data as much as its quality, and that it should focus more on the representativeness of data, and on model architecture, design, and training. 相似文献
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为研究中文学术论文下载次数与语言学特征的关系,文章以图书情报学领域被CSSCI收录的7种期刊发表于2014-2017年的6,257篇学术论文为研究对象,选用8个语言学特征指标测度高下载论文(Top 20%)、低下载论文(Bottom 20%)和全体论文的语言学特征。从中值和均值来看,各期刊高下载论文的标题长度几乎都小于总体论文和低下载论文,摘要词汇多样性、正文长度、正文句子长度和正文词汇多样性整体上大于总体论文和低下载论文。从显著性检验结果来看,整体上未通过显著性检验,但特定平台特定期刊的特定语言学特征指标通过了显著性检验。从样本数据来看,整体上语言学特征对中文学术论文下载次数影响很小,但在特定平台特定期刊语言学特征具有一定影响。 相似文献
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[目的/意义]在当今数字网络、知识经济和大数据背景下,"五计学"学科群表现出一些新的发展特征和发展趋势,"五计学"领域出现了新现象和新问题,需要采用新思维和新方法来研究和解决"五计学"研究成果,整合"五计学"研究方法,为"五计学"的融合发展指明方向。[方法/过程]本文运用内容分析法与归纳演绎法对相关研究进行分析。[结果/结论]尝试性地提出了6种"五计学"知识融合实现模式:基于语义规则的知识融合,基于贝叶斯网络的知识融合,基于D-S理论的知识融合,基于知识挖掘的知识融合,面向网格环境的知识融合以及面向近似知识的知识融合;提出了2种"五计学"知识融合过程控制手段分别是知识融合评价和知识融合系统。 相似文献
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大量证据显示,以知识产权商业化为代表的"技术转移"模式仅仅是大学和企业互动关系中的"冰山一角",许多非正式的合作行为被掩盖。本文根据创新研究最新观点,采用更为全面的谱系描述产学研合作中的"知识转移"行为,并重点比较了UNICO报告和IPRIA报告是如何分别设计指标以测量知识转移行为和知识转移效果。借助这一框架体系,进一步分析了中国相应数据的可得性,并提出完善数据采集工作的建议。 相似文献