专利被引频次的时间影响研究     

罗文馨  赵亚娟 《图书情报工作》2019,63(9):47-60

[目的/意义]研究时间因素对专利被引频次的影响,可以减少时间因素对技术评价活动的制约,提高评价的准确性和可信度。[方法/过程]采集1975-2017年的美国专利数据,开展基于固定效应法的专利被引频次的修正研究。将专利按照不同公开年份和不同技术领域分组,选定组内均值和6个TOP分位数为被引频次基准,统计当前时间点的被引频次基准线及基准线的历史时序变化情况。建立神经网络模型,拟合基准线的时序变化规律,并预测未来统计时间点的基准线。[结果/结论]专利公开年份和统计年份的时间差异,使得专利被引频次无法直接进行比较。本文建立了基于不同技术领域、不同公开年份和不同统计年份的专利被引频次基准线,为专利评估提供参考。  相似文献   

高职院校学习预警平台的构建及其实证分析     

宋楚平  李少芹  蔡彬彬 《现代教育技术》2020,(5):94-100

开展信息化、智慧化预警工作是实现全面精准育人的重要途径,而预警应用平台无疑是预警工作的有力工具和实践载体,其设计方案应用效果的好坏直接决定着学习预警信息化愿景的达成度。文章在分析高职院校学习预警工作现状的基础上,从工作流程设计、平台框架设计和平台建设方法等3个方面提出了解决方案,并对平台的应用效果进行了实证分析,结果表明:平台的应用扩展了预警范围、提升了预警的精准度和时效性、提高了工作效率,且干预更为灵活、个性化,可为当前高职院校学习危机的实践改革提供新思路。  相似文献   

灰色预测法在情报研究中的应用研究综述     

张晶晶  李泽霞 《图书情报工作》2020,64(24):106-114

[目的/意义] 灰色预测法可有效处理情报研究中广泛存在的小样本数据，通过对灰色预测法在情报研究中的应用情况进行梳理，总结其在应用过程中存在的不足，为灰色预测法在情报研究中的进一步应用提供参考。[方法/过程] 通过综述情报研究中涉及灰色预测法的相关文献，从数据选取、模型构建和解决的问题等方面对情报研究中灰色预测法的应用进行概述，总结当前情报研究中灰色预测法的应用所存在的问题，并提出改进建议。[结果/结论] 在方法应用上，已有研究主要采用数列灰预测，且模型集中在单变量灰色预测模型，根据预测对象不同，灰色预测法已经在包括期刊分析、图书馆运行管理、热点主题分析及科研机构评价方面得到了很好的应用，未来可根据预测对象特点及研究目标尝试不同的灰色预测方法，扩宽灰色预测法在其他方面的情报研究问题中的应用。  相似文献   

Quality flaw prediction in Spanish Wikipedia: A case of study with verifiability flaws     

Edgardo Ferretti  Leticia Cagnina  Viviana Paiz  Sebastián Delle Donne  Rodrigo Zacagnini  Marcelo Errecalde 《Information processing & management》2018,54(6):1169-1181

In this work, we present the first quality flaw prediction study for articles containing the two most frequent verifiability flaws in Spanish Wikipedia: articles which do not cite any references or sources at all (denominated Unreferenced) and articles that need additional citations for verification (so-called Refimprove). Based on the underlying characteristics of each flaw, different state-of-the-art approaches were evaluated. For articles not citing any references, a well-established rule-based approach was evaluated and interesting findings show that some of them suffer from Refimprove flaw instead. Likewise, for articles that need additional citations for verification, the well-known PU learning and one-class classification approaches were evaluated. Besides, new methods were compared and a new feature was also proposed to model this latter flaw. The results showed that new methods such as under-bagged decision trees with sum or majority voting rules, biased-SVM, and centroid-based balanced SVM, perform best in comparison with the ones previously published.  相似文献   

基于二模复杂网络的隐性知识发现方法研究——以潜在药物靶点挖掘为例     

李东巧  陈芳  韩涛  杨艳萍  王学昭  王燕鹏  Cynthia Liu  Yingzhu Li 《图书情报工作》2020,64(21):120-129

[目的/意义] 通过构建二模复杂网络模型，揭示隐藏在海量文献中的隐性知识。[方法/过程] 通过NetworkX复杂网络工具包，依据任意两个节点的共现关系构建二模复杂网络模型；对网络模型中节点的共现关系进行加权，计算网络的拓扑信息并进行AP聚类，提取节点间的直接关系；采用AUC方法对AA、JC、加权改进的wAA和wJC等4种链路预测算法进行评价，遴选出最合适的预测算法，并对复杂网络的隐性关系进行预测分析。[结果/结论] 以潜在药物靶点挖掘为例进行的实证研究结果表明，wAA链路预测算法为最优的链路预测算法；二模复杂网络模型、指标和方法体系在美国化学文摘社数据库中的药物靶点挖掘中具有一定的有效性。下一步计划在其他数据库中或其他研究领域中进行尝试，以进一步验证该模型的通用性和有效性。  相似文献   

Digital Module 16: Longitudinal Data Analysis     

Jeffrey R. Harring  Tessa L. Johnson 《Educational Measurement》2020,39(3):137-138

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module begins with a nontechnical overview of longitudinal data analyses drawing distinctions with cross-sectional analyses in terms of research questions to be addressed. Nuances of longitudinal designs, timing of measurements, and the real possibility of missing data are then discussed. The three interconnected components of the LME model—(1) a model for individual and mean response profiles, (2) a model to characterize the covariation among the time-specific residuals, and (3) a set of models that summarize the extent that individual coefficients vary—are discussed in the context of the set of activities comprising an analysis. Finally, they demonstrate how to estimate the linear mixed effects model within an open-source environment (R). The digital module contains sample R code, diagnostic quiz questions, hands-on activities in R, curated resources, and a glossary.  相似文献   

Cross-company customer churn prediction in telecommunication: A comparison of data transformation methods     

《International Journal of Information Management》2019

Cross-Company Churn Prediction (CCCP) is a domain of research where one company (target) is lacking enough data and can use data from another company (source) to predict customer churn successfully. To support CCCP, the cross-company data is usually transformed to a set of similar normal distribution of target company data prior to building a CCCP model. However, it is still unclear which data transformation method is most effective in CCCP. Also, the impact of data transformation methods on CCCP model performance using different classifiers have not been comprehensively explored in the telecommunication sector. In this study, we devised a model for CCCP using data transformation methods (i.e., log, z-score, rank and box-cox) and presented not only an extensive comparison to validate the impact of these transformation methods in CCCP, but also evaluated the performance of underlying baseline classifiers (i.e., Naive Bayes (NB), K-Nearest Neighbour (KNN), Gradient Boosted Tree (GBT), Single Rule Induction (SRI) and Deep learner Neural net (DP)) for customer churn prediction in telecommunication sector using the above mentioned data transformation methods. We performed experiments on publicly available datasets related to the telecommunication sector. The results demonstrated that most of the data transformation methods (e.g., log, rank, and box-cox) improve the performance of CCCP significantly. However, the Z-Score data transformation method could not achieve better results as compared to the rest of the data transformation methods in this study. Moreover, it is also investigated that the CCCP model based on NB outperform on transformed data and DP, KNN and GBT performed on the average, while SRI classifier did not show significant results in term of the commonly used evaluation measures (i.e., probability of detection, probability of false alarm, area under the curve and g-mean).  相似文献   

女子大众艺术健身操锻炼效果的实验研究   总被引：9，自引：0，他引：9  

袁尽州  黄海 《西安体育学院学报》2003,20(1):66-68

以 6 0名 18岁以上女子为研究对象 ,采用自编的四套大众艺术健身操 ,每周进行三次练习 ,每次 6 0分钟。持续练习 8周。结果表明 :大众艺术健身操练习可以减小女子身体各部位的围度 ,具有改善女子的形体特征的作用。不仅有非常明显的减肥作用 ,而且具有增加瘦体重从而改变身体成分 ,达到增强体质的作用。对于体重超重和肥胖者 ,减肥和降体重 ,改善身体成分的作用更为显著。大众艺术健身操对提高女子呼吸系统、循环系统机能水平也有一定的作用。对提高女子的力量、灵敏性、平衡能力及反应速度等身体素质有显著的作用。  相似文献   

跳远助跑速度变化对起跳效果的影响——国内外优秀运动员与我院选手的比较分析   总被引：1，自引：0，他引：1  

程万才 《西安体育学院学报》2003,20(2):78-79

笔者采用高速摄影、影片解析、数理统计等方法对西安体育学院男子跳远运动员和国内外优秀选手助跑速度变化而影响起跳效果的因素进行比较研究。结果表明:跳远助跑各段落速度的变化对起跳效果及成绩产生很大影响;西安体育学院男子跳远运动员绝对速度低,起跳前两步速度、速度利用率呈下降趋势,影响起跳初速度;跳远起跳前一步的速度、速度利用率对提高起跳效果要比起跳前9—10m段的速度、速度利用率更具有实际意义。  相似文献   

台阶试验质疑   总被引：62，自引：1，他引：61  

王健  邓树勋 《中国体育科技》2003,39(2):61-64

台阶试验是一项由BROHA建立的用以评价机体对强体力负荷的适应能力和身体机能的恢复能力的运动负荷试验,研究表明:台阶试验指数与运动耐力和最大耗氧量之间无高度相关,因此,不能对心血管系统功能作出准确评价;台阶试验指数只能够对受试者的状况作出好与不好的评价,而不能作出精确评价;台阶试验指数不能有效反映以最大耗氧量、最大心输出量为代表的心脏功能增龄性变化规律及其性别差异。鉴于以上原因,台阶试验作为心血管系统功能评价的运动负荷试验尚待进一步研究。  相似文献