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prediction study for articles containing the two most frequent verifiability flaws in Spanish Wikipedia: articles which do not cite any references or sources at all (denominated Unreferenced) and articles that need additional citations for verification (so-called Refimprove).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   

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   

人体上下肢长预测方法的研究与应用     

田文秀 《山东体育学院学报》2004,20(3):60-61

人体生长发育过程中，具有非等比性和向心律的特点，在生长发育结束以前测评出的形态比例关系，不能直接说明成熟后的情况。通过对7～18岁儿童少年发育状况的调研，提出了人体上下肢长与身高比例关系的预测方法。  相似文献   

关于影响蔡民十项全能主要因素的分析及成绩的预测研究     

张杏波 《浙江体育科学》2004,26(2):89-90,96

应用灰色系统对十项全能的影响因素进行了分析,找出了影响其成绩变化的优势因素.并运用灰色动态模型进行了近期和短期的预测,结果证明这一方法对十项成绩的预测准确性较好,残差一般为±0.25% .  相似文献   

商务英语专业学生英语阅读理解常见错误的实证研究     

崔文尖 《珠海城市职业技术学院学报》2006,12(1):15-24

文章通过对高职商务英语专业学生阅读中难句翻译理解错误的分析及其与阅读理解得分之间的相关分析，发现翻译错误与阅读理解高度正相关；母语参与阅读理解思维活动有利于学习者对原文的理解；在影响学习者阅读理解的各因素中，词汇影响最大；中国学生在阅读理解中，对某些结构和词汇的省略并不会对阅读理解造成重大影响。  相似文献   

销售量预测模型及其应用   总被引：3，自引：0，他引：3  

王丰效 《天水师范学院学报》2002,22(5):19-20

运用回归分析方法建立的某类销售量预测模型,对季节变化关联较强的商品的销售量有较高的预测精确度。  相似文献   

融合深度学习和链路预测的细粒度技术预测研究——以合成生物技术为例     

胡雅敏  吴晓燕  廖兴滨  钱杨舸  陈方 《图书情报工作》2022,66(24):92-103

[目的/意义]面向专利文本进行更细粒度的技术实体识别和技术预测,利于更详细地把握专利技术布局与趋势。[方法/过程]首先利用深度学习方法自动识别专利技术术语类实体,通过实验对比多组深度学习算法的优劣。其次,提出新的半监督标注和自定义标注方案,提高人工标注效率。最后,执行训练得到的最优模型,结合链路预测方法,对合成生物技术进行细粒度的技术预测。[结果/结论]实证结果表明RoBERTa-BiLSTM-CRF模型更适用于语义复杂的专利技术实体识别,F1值可达到86.8%,技术识别结果比传统IPC分析方法更精细。同时,细粒度的技术预测结果表明,合成生物学的合成方法在不断改进创新,合成物研究向合成燃料发展。  相似文献   

Quiet eye training aids the long-term learning of throwing and catching in children: Preliminary evidence for a predictive control strategy     

C. A. L. Miles  S. J. Vine  J. N. Vickers  M. R. Wilson 《European Journal of Sport Science》2017,17(1):100-108

Abstract

Quiet eye training (QET) may be a more effective method for teaching children to catch than traditional training (TT) methods, but it is unclear if the benefits accrued persist in the long term. Thirty children were randomly allocated into a QET or TT group and, while wearing a mobile eye tracker, underwent baseline testing, training and two retention tests over a period of eight weeks, using a validated throw and catch task. During training, movement-related information was provided to both groups, while the QET group received additional instruction to increase the duration of their targeting fixation (QE1) on the wall prior to the throw, and pursuit tracking (QE2) period on the ball prior to catching. In both immediate (R1) and delayed (R2, six weeks later) retention tests, the QET group had a significantly longer QE1 duration and an earlier and longer QE2 duration, compared to the TT group, who revealed no improvements. A performance advantage was also found for the QET compared to the TT group at both R1 and R2, revealing the relatively robust nature of the visuomotor alterations. Regression analyses suggested that only the duration of QE1 predicted variance in catch success post-training, pointing to the importance of a pre-programming visuomotor strategy for successful throw and catch performance.  相似文献