基于读者属性分析的图书馆空间再造研究

[目的/意义]现阶段很多图书馆都出现了空间不足、环境老化的现象,空间再造成为图书馆的一个迫在眉睫、亟待解决的重大课题。[方法/过程]根据图书馆空间五要素要求原则,从读者属性角度分析图书馆空间短缺的原因是来自读者对图书馆空间的需求差异,把握读者属性的特点才能更好的进行空间再造。[结果/结论]针对不同类型的图书馆给出有效改善图书馆空间紧缩或阅读空间空置率高等现状的相应思路。     

How U.S. and Chinese journalists think about plagiarism

A comparison of 1,096 professional journalists in China and the United States on attitudes toward attribution and plagiarism reveals Chinese journalists were more likely to see attribution as a practice to be embraced regardless of career longevity and culture, suggesting journalistic norms are more important than a collectivist orientation. Attribution was more likely to be embraced by those who see principles as more important than expediency, affirming research that plagiarism is hardly a monolithic concept. Overall, journalists in the two nations did not vary significantly in their attitudes toward plagiarism, despite vast differences in culture and politics as well as evidence that in some other fields China is more accepting of reusing material without attribution. The data show that among journalists, attitudes toward plagiarism are shared across national boundaries, reinforcing related research showing that a journalism culture exists and is shared at least in part across national boundaries.     

智慧图书馆建设误区与建设策略

[目的/意义] 探究构建智慧图书馆的主要策略,回答什么是智慧图书馆,智慧图书馆是什么样式,建设智慧图书馆的策略,解决智慧图书馆建设中一些模糊不清的理论与实践问题,以拓宽视野。[方法/过程] 采用文献调研与实地调研相结合,梳理和分析图书馆发展历程,指出智慧图书馆建设中出现的误区,提出建设策略。[结果/结论] 提出构建智慧图书馆五大策略,即整体的目标分析与设计;从数据到大数据;多元数据的融合;协调合作与分步落地;创新环境营造。     

CrossCheck检测平台及信息核实在学术不端防治中的作用

采用CrossCheck检测平台(http://www.ithenticate.com/)对英文科技论文进行比对,通过分析查重比对结果可初步判断该论文是否涉嫌学术不端,进而判断该论文的新颖性和研究热门程度.查重比对可为编辑处理稿件提供有力的支持,为审者审稿提供必要的参考,以便给出公正的审理意见.另外,讨论了审者信息及作者信息的核实对干预学术不端行为的作用.     

基于DEMATEL模型的我国政府信息资源跨部门共享的关键影响因素研究

[目的/意义] 新时代下,跨部门的信息资源共享已经成为加快政府职能转变,提高政府服务效率和透明度的重要事业。明确目前政府信息资源共享有效实施的关键因素,无论对于政府准确把脉行动方向还是学界聚焦政府信息共享的根源性问题都有着重要的意义。[方法/过程] 通过综合集成法梳理出近年来被学界所关注的8个维度的政府信息资源共享影响因素,通过复杂系统DEMATEL模型,构建政府信息资源共享影响因素的关系矩阵。[结果/结论] 经测算,本研究发现11个影响政府信息资源共享实施的关键因素,这些关键因素主要集中在法规政策与标准维度、体制维度、机制维度和技术维度上。     

试析数据新闻生产中的个人数据滥用与规避

在数据新闻生产中,数据新闻记者对个人数据的二次利用渐成常态,一些数据新闻作品本身就是涉及特定群体的个人数据库.文章总结了记者采集个人数据的四种方式:开放获取、申请获取、自行采集和共享获取.然而在数据新闻生产中也存在个人数据滥用行为,如未经同意的个人数据采集、个人隐私侵犯和个人数据的过度挖掘等.知情同意原则、合法适度原则、公共利益优先与最小伤害原则可以有效解决个人数据的保护与利用问题.     

Using word embeddings in Twitter election classification

Word embeddings and convolutional neural networks (CNN) have attracted extensive attention in various classification tasks for Twitter, e.g. sentiment classification. However, the effect of the configuration used to generate the word embeddings on the classification performance has not been studied in the existing literature. In this paper, using a Twitter election classification task that aims to detect election-related tweets, we investigate the impact of the background dataset used to train the embedding models, as well as the parameters of the word embedding training process, namely the context window size, the dimensionality and the number of negative samples, on the attained classification performance. By comparing the classification results of word embedding models that have been trained using different background corpora (e.g. Wikipedia articles and Twitter microposts), we show that the background data should align with the Twitter classification dataset both in data type and time period to achieve significantly better performance compared to baselines such as SVM with TF-IDF. Moreover, by evaluating the results of word embedding models trained using various context window sizes and dimensionalities, we find that large context window and dimension sizes are preferable to improve the performance. However, the number of negative samples parameter does not significantly affect the performance of the CNN classifiers. Our experimental results also show that choosing the correct word embedding model for use with CNN leads to statistically significant improvements over various baselines such as random, SVM with TF-IDF and SVM with word embeddings. Finally, for out-of-vocabulary (OOV) words that are not available in the learned word embedding models, we show that a simple OOV strategy to randomly initialise the OOV words without any prior knowledge is sufficient to attain a good classification performance among the current OOV strategies (e.g. a random initialisation using statistics of the pre-trained word embedding models).     

物理课的预习方法

物理课的预习是课堂学习的“添加”和“催化”剂,现给同学们介绍几种预习方法,供参考。1标号法在上新课之前,大家应认真阅读新课,并且在课文中的重点句子下面标符号。例如,在预习《光的直线传播》这一课时,在“光在同一种物质里传播的路线是直的”这句话中“同一种物质”,“直”这六个字下面画小黑点,或画红线。又如在预习《电压》这一课时,对“电压是使自由电荷发生定向移动形成电流的原因”这句话不理解,可在这句话的后面画一个问号,以便上课时集中精力听老师讲解其含义,或者向老师提出此问题,请老师解答。2分析法上新课前同学们应根据本…     

关于算子(.V)的广义四则运算的图象实现

本文主要给出实数集R上的一般Fuzzy集关于算子(·V)的四则运算的作图方法.