有关普通话水平测试中一乙等级评分的几点感想

教育部颁布了新的<普通话水平测试管理规定>对普通话测试提出了新的要求,针对"一级乙等"测试中存在的问题和现象,笔者提出了粗浅的见解以期和同仁共同探讨.     

中国画临摹与创作

本文主要阐述临摹是学习中国画技能的一条有效的道路,是创作的必经之路。中国画许多大师都是从临摹起步的,像张大千、黄秋园等,也是从临摹筑基的,而后创作出自己绘画风格的。临摹中正确的学习方法体现出了悟性的高低,因此掌握正确的方法是进步的关键。艺术的最终目的是创作,临摹学习都是在为创作打基础的。而创作也需要有成熟的笔墨技法,技法的训练就是通过临摹来成熟的。所以临摹与创作是相辅相成的。     

促进学生理解的学习:价值、内涵及教学启示

促进学生对知识的理解是一个公认的教育命题,但在实践中往往因对这个命题本身认识的不深刻与不全面而造成实践走样与效果疏离。共同的困惑促成了全球教育界对该课题研究的逐步关注。借助学习科学的理论体系,理解的内涵被赋予了崭新的面貌。以学习为支点,研究者找到了其在教育领域中的真正用武之地。对理解的价值及内涵的探究与明晰,对教师的教学实践乃至我国课程与教学改革极具启迪与指导意义。     

Improving the precision of the keyword-matching pornographic text filtering method using a hybrid model

With the flooding of pornographic information on the Internet, how to keep people away from that offensive information is becoming one of the most important research areas in network information security. Some applications which can block or filter such information are used. Approaches in those systems can be roughly classified into two kinds:metadata based and content based. With the development of distributed technologies, content based filtering technologies will play a more and more important role in filtering systems. Keyword matching is a content based method used widely in harmful text filtering. Experiments to evaluate the recall and precision of the method showed that the precision of the method is not satisfactory, though the recall of the method is rather high. According to the results, a new pornographic text filtering model based on reconfirming is put forward. Experiments showed that the model is practical, has less loss of recall than the single keyword matching method, and has higher precision.     

关于对严复的"信、达、雅"的认识

严复的"信、达、雅"三难说对翻译标准进行了高度的概括。"信、达、雅"蕴涵着丰富的辩证法思想,"信"是最基本的,指译者要如实地表达原文的意思,"达"是指译文要顺畅,"雅"是指译文要有文采。"三难说"主次有序,既提出了"达"对"信"的制约,又提出了"雅"对"信"和"达"的影响,三者构成了一个统一的有机体。     

译者主体的创造性

译作为翻译活动的主体，应在翻译中发挥其能动参与和积极的创造性作用。本提出“衍生本”的概念，并从译创造性产生的前提、根源和具体实现方式这三个方面论证了译主体创造性的客观存在，认为只有正视这种创造性的客观存在并对其加以积极运用．才能正确地指导翻译活动的进行。     

Personalized learning in iSTART: Past modifications and future design

Abstract

Computer-based learning environments (CBLEs) provide unprecedented opportunities for personalized learning at scale. One such system, iSTART (Interactive Strategy Training for Active Reading and Thinking) is an adaptive, game-based tutoring system for reading comprehension. This paper describes how efforts to increase personalized learning have improved the system. It also provides results of a recent implementation of an adaptive logic that increases or decreases text difficulty based on students’ performance rather than presenting texts randomly. High school students who received adaptive text selection showed increased sense of learning. Adaptive text selection also resulted in greater pre-training to post-training comprehension test gains, especially for less-skilled readers. The findings demonstrate that system-driven, just-in-time support consistent with the goals of personalized learning benefit the efficacy of computer-based learning environments.     

基于文本挖掘和技术路线图的技术创新机会发现

本文在介绍文本挖掘和技术路线图研究情况的基础上，探讨如何将文本挖掘和技术路线图结合起来，通过挖掘隐含在科技信息中的知识和联系，并结合技术领域专家，绘制技术路线图，以帮助技术主管发现技术创新的机会。     

过刊全文数据库JSTOR及其特色分析

基于因特网的电子期刊的出版 ,过去比较多地集中在现刊上。但是近年来越来越多的出版商或专业人士意识到 ,实际上许多早年发表的学术论文并没有随着时间的推移而失去其使用价值 ,它们的“有效期”超过人们已有的估计。有统计表明 ,最常被引用的 10篇经济学论文 ,它们的发表时间平均距现在 15年以上 ;而最常被引用的数学论文的发表时间平均距现在 30年以上[1] 。基于这样的认识 ,开始有人把注意力放在学术性期刊过刊全文数据库的开发上 ,例如ElsevierScience出版公司的过刊文档项目(BackfileProject) ,就是要逐步将其出版的所有期刊全部电…     

A hybrid generative/discriminative approach to text classification with additional information

This paper presents a classifier for text data samples consisting of main text and additional components, such as Web pages and technical papers. We focus on multiclass and single-labeled text classification problems and design the classifier based on a hybrid composed of probabilistic generative and discriminative approaches. Our formulation considers individual component generative models and constructs the classifier by combining these trained models based on the maximum entropy principle. We use naive Bayes models as the component generative models for the main text and additional components such as titles, links, and authors, so that we can apply our formulation to document and Web page classification problems. Our experimental results for four test collections confirmed that our hybrid approach effectively combined main text and additional components and thus improved classification performance.