Guiding students to the right questions: adaptive navigation support in an E‐Learning system for Java programming

Rapid growth of the volume of interactive questions available to the students of modern E‐Learning courses placed the problem of personalized guidance on the agenda of E‐Learning researchers. Without proper guidance, students frequently select too simple or too complicated problems and ended either bored or discouraged. This paper explores a specific personalized guidance technology known as adaptive navigation support. We developed JavaGuide, a system, which guides students to appropriate questions in a Java programming course, and investigated the effect of personalized guidance a three‐semester long classroom study. The results of this study confirm the educational and motivational effects of adaptive navigation support.     

一种面向突发事件的文本语料自动标注方法

事件语料库是研究语义Web中事件知识的抽取、表示、推理和挖掘的基础和关键技术之一。该文以事件作为文本知识单元,在LTP分析的基础上,用序列模式挖掘算法PrefixSpan从现有的小规模语料库中挖掘事件要素的词性规则等,用同义词词林(扩展版)对触发词表进行了扩充,结合自定义的事件要素词典,采用多遍过滤、逐遍完善的思想提出一种针对大规模突发事件语料库构建的自动标注方法,在实验部分不仅与人工标注做了对比,同时与Stanford CoreNLP NER进行了对比,实验效果理想。     

《现汉》与《语法信息词典》词类对应分析

词类标注问题历来受到中文信息处理、汉语语法和词汇学界的共同关注,学者们已提出多种词类标记体系,彼此间存在较大差异,但迄今尚无人对大规模词类标注工程进行系统比较。该文以《现代汉语词典》第5版和《现代汉语语法信息词典》两个大型词典词类标注工程为比较对象,基于所提出的词类对应算法,自动找出两部词典词类标注上的差异,进而对形成差异的原因进行分析。分析结果表明,两部词典词类标注一致性较高(83.5%完全相同),而存在差异的地方可归结为三类主要原因: 词类迁移;词类判断标准不一致;收录义项不同。     

图像与视频自动标注最新进展

近年来,图像与视频自动标注技术成为多媒体信息处理领域的一个研究热点并且发展迅速。重点介绍此领域研究的最新进展。将这些新方法分为两类:基于学习的标注方法和基于搜索的标注方法,分别介绍了各个算法的基本思想和优缺点。然后,介绍了一些目前流行的商业的和研究性的图像检索及标注系统。最后,提出了自动标注技术的进一步研究方向。     

Zodiac: A history-based interactive video authoring system

Easy-to-use audio/video authoring tools play a crucial role in moving multimedia software from research curiosity to mainstream applications. However, research in multimedia authoring systems has rarely been documented in the literature. This paper describes the design and implementation of an interactive video authoring system called Zodiac, which employs an innovative edit history abstraction to support several unique editing features not found in existing commercial and research video editing systems. Zodiac provides users a conceptually clean and semantically powerful branching history model of edit operations to organize the authoring process, and to navigate among versions of authored documents. In addition, by analyzing the edit history, Zodiac is able to reliably detect a composed video stream's shot and scene boundaries, which facilitates interactive video browsing. Zodiac also features a video object annotation capability that allows users to associate annotations to moving objects in a video sequence. The annotations themselves could be text, image, audio, or video. Zodiac is built on top of MMFS, a file system specifically designed for interactive multimedia development environments, and implements an internal buffer manager that supports transparent lossless compression/decompression. Shot/scene detection, video object annotation, and buffer management all exploit the edit history information for performance optimization.     

MTranslatability

Machine Translation of arbitrary input is difficult,but the output quality can be improved significantlyif writers create documents with MT in mind. Thisarticle deals with ``MTranslatability' – translatabilityof texts by MT systems. It identifies characteristics oftext that decrease MTranslatability and suggests waysto improve them. It also illustrates the effect of writingfor MTranslatability by showing before-and-after picturesof output from various commercially available MT systems,and gives an overview of tools that help identify and correctthe problems.     

一种基于多核函数SVM的图像标注方法

针对多项式核或RBF核SVM不能很好地处理图像标注中的数据不平衡问题,提出了一种基于多核函数SVM的图像标注方法,该方法采用多核函数训练过的SVM将基于区域的图像标注问题转化为对非平衡数据分类的问题,进而对图像标签进行分类以获取更符合图像真实含义的标注.实验结果表明,多核函数SVM图像标注性能优于单独使用局部或全局核函数.     

郑玄《诗经》笺及《三礼》注疑问句的研究

郑玄为《诗经》《三礼》所作笺注中的疑问句,反映了东汉末期疑问句的特点。从郑注看,其疑问句中的疑问词出现了双音化现象,疑问标记三重复用现象也有所增多,疑问代词"何"也成为了较高层级的疑问标记。     

利用Ontology改进的自动化图像标注方法

图像检索系统大多是利用图像的底层特征如颜色、纹理和图像来分析图像,没有考虑图像内容及其对象的内容语义,导致对图像的理解不佳.为使系统能更准确的理解图像中的对象及其深层语义,分析了目前图像标注的优缺点,提出了一种以底层特征为基础,利用本体论建构的知识辅助计算机分析图像中实体对象,判断对象与对象间在现实世界中存在的合理相关性,进而对图像进行标注.实验结果显示加入本体论辅助标注图像大大提高了图像识别的准确性.