揭开神秘的面纱--评《神话与现实-〈一千零一夜〉论》

郅溥浩所著《神话与现实-<一千零一夜>论》是我国第一部以多层次、多视角研究阿拉伯民间文学《一千零一夜》的专著。作者首先追本溯源,解析《一千零一夜》的成书之谜;其次在国际民间故事研究的宏大视野下,考察其故事母题和故事类型的特点;再用微观求证的方法,以文化参与的开阔视点深入挖掘文本的丰富文化内涵并探究其双重价值取向;最后在宏观的视野下考察其世界地位。     

汉语个体量词的产生及其原因探讨

从历时的角度考察了汉语个体量词产生、发展和成熟时期的情况,和汉语个体量词产生的动因。认为汉语个体量词的产生是汉语范畴化和汉语类型特点制约的结果,同时反映了汉民族的认知视点。     

流媒体课件中流式素材的制作

探讨了流媒体课件中流式素材的制作，主要论述了流式文本、流式音频和流式视频素材的制作方法与制作技巧。给出了具体的制作实例，分析了流化的过程和流式文件的有关属性。     

社会学批评的一种成功实践--王彬彬批评读解

当代著名批评家王彬彬往往以社会学批评方法从事批评实践活动，表现出三方面主要特色：儒宰的入世精神和浩然正气；对道德与人文精神的坚持和对现实的批判；学理性和文学性俱佳的文本形式。他取得了一定的成就，在当代文学批评中自成一家。     

影视字幕文本特征及其翻译策略

论文以当下流行美国影视作品为例,分析了影视字幕的文本特征,总结影视字幕文本的翻译技巧与策略,切实提高影视作品字幕翻译的效率,有效缩短了由语言差异性带来的文化距离.     

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。     

文本知识的自动分类方法初探

本文结合运用信息管理和人工智能的原理与技术，探讨了文本知识的自动分类方法，包括：自动归类与聚类方法、基于实例的学习分类方法和基于特征值的元学习方法。     

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.