Computer software as text

Participatory design strategies have placed the user at the center of the design process, leaving computer software designers without guidelines for how to design and implement the software system. This paper aims to bring the designer back to the center of the design process. and the way of doing it is to consider computer software as text. Three different text theories are presented in order to explain what is meant by text, namely pragmatics, structuralism and deconstructivism. Finally it is discussed how the design processes should be understood, and how they should be organized when taking the text point of view of computer software.     

Scene text reading based cloud compliance access

World Wide Web - Cloud Compliance Access system assure that cloud users could utilize resources of cloud platform while conforming to regulations and the specific functions of this system were User...     

脏话文本语料库建设

脏话作为一种非正规的语言现象,在网络评价中已经无处不在,对网络文明造成了影响。描述了脏话文本的特点、定义及其危害,并对网络脏话文本进行了研究与分析,设计了一个机器自动判别与少量人工标注相结合的脏话语料采集方法,借助海量的真实评价文本,构造了一个较大规模的高质量的脏话语料库,初步采集了6 000多句脏话语料。然后利用一元、二元和三元特征,通过SVM与最大熵分类器对脏话的自动分类进行了实验,结果表明,两种分类器的准确率和查全率都达到97%以上。     

Human performance evaluation of user interfaces for spatially-constrained text portrayal and access

To maximize visualization effectiveness, graphical data are commonly augmented with text to provide detailed information and define specific values. This text is often displayed in a pop-up dialog box pertaining to an object, permitting simultaneous display of the object and associated alphanumeric information. However, a human operator performance cost may be incurred when the resulting portrayal occludes critical information within the visualization. To address this issue, we developed and evaluated three alternative, spatially constrained, text portrayal techniques. These techniques and their associated access interface were designed to reduce occlusion while providing rapid access to desired alphanumeric data. Each technique was evaluated against the pop-up dialog using a dual-task human performance paradigm. Performance measures included accuracy, response time, display occlusion, and subjective feedback. The basis for the spatially-constrained text access technique design, their implementation affordances, and limitations are discussed. The alternative techniques and their user interface concepts resulted in mixed accuracy and response time performance compared to the pop-up dialog. Specific design features reduced data access time to one third of the time required to access the spatially-constrained text access techniques. Overall, equivalent performance was obtained among the variants while the potential for occlusion was reduced during use of the novel designs.     

Computer usage and access in low-income urban communities

The purpose of this study is to examine the effects of home computer access on low-income families participating in the Computer for Families program. The study focused on participants (1) general computer usage, access and knowledge; (2) employment; (3) education; and (4) their children’s-computer access, usage and academic performance. The study methodology consisted of a quasi-experimental design using qualitative and quantitative approaches, including focus groups, pretests and post-tests, and self-reported surveys with experimental and control groups. Statistically significant findings suggest that participants in the Computers for Families program were more likely than non-participants to have access to the Internet from home, use a computer for more than 1 h per day, complete online job applications, and submit job applications and resumes electronically. Social and behavioral implications regarding computer access and usage in low-income urban communities are discussed.     

基于文本挖掘获取相关角色授权问题研究

如何满足人们合理的个性化需求,实现信息资源的按需分配为目的,是数字化校园建设的核心。在数字校园中,不同群体提供的信息服务是不同的。因此,存在着对信息服务对象的甄别的问题。本文从一个特殊的群体--行政管理群体出发,结合现有的电子政务系统,对电子文本进行挖掘获取相关角色及授权,实现角色及授权管理的时效性、真实性,杜绝了人为因素的影响。     

Computer access and student achievement in the early school years

Abstract This study examines the assumption that optimal learning occurs in classrooms where every child has access to their own computer. Grades 1 to 4 classrooms in seven schools of an urban school district were given laptop computers in three different student-to-computer ratios (1 : 1, 2 : 1, 4 : 1). Throughout the school year three samples of student writing were taken at equal intervals and classrooms were regularly observed. Writing samples were also collected from control classrooms in the same schools that did not have access to computers. A mancova analysis of holistic ratings of writing samples revealed that by the end of the school year students in the 2 : 1 ratio classrooms improved significantly more than their counterparts in the other groups; the control group students demonstrated the least improvement, while the 1 : 1 and 4 : 1 groups showed intermediate levels of improvement. The study concludes by questioning the long-range efforts at equipping schools with one computer for every student.     

Computer access for persons who are blind or visually impaired: human factors issues

Suitably adapted computers hold considerable potential for integrating people who are blind or visually impaired into the mainstream. The principal problems that preclude the achievement of this potential are human factors issues. These issues are discussed, and the problems presented by icon-based interfaces are reviewed. An argument is offered that these issues, which ostensibly pertain to the blind or visually impaired user, are fundamental issues confronting all users. There is reason to hope that the benefits of research into the human factors issues of people with vision impairments will also extend to the sighted user.     

Automatic text segmentation and text recognition for video indexing

Efficient indexing and retrieval of digital video is an important function of video databases. One powerful index for retrieval is the text appearing in them. It enables content-based browsing. We present our new methods for automatic segmentation of text in digital videos. The algorithms we propose make use of typical characteristics of text in videos in order to enable and enhance segmentation performance. The unique features of our approach are the tracking of characters and words over their complete duration of occurrence in a video and the integration of the multiple bitmaps of a character over time into a single bitmap. The output of the text segmentation step is then directly passed to a standard OCR software package in order to translate the segmented text into ASCII. Also, a straightforward indexing and retrieval scheme is introduced. It is used in the experiments to demonstrate that the proposed text segmentation algorithms together with existing text recognition algorithms are suitable for indexing and retrieval of relevant video sequences in and from a video database. Our experimental results are very encouraging and suggest that these algorithms can be used in video retrieval applications as well as to recognize higher level semantics in videos.     

Automatic text categorization and its application to text retrieval

We develop an automatic text categorization approach and investigate its application to text retrieval. The categorization approach is derived from a combination of a learning paradigm known as instance-based learning and an advanced document retrieval technique known as retrieval feedback. We demonstrate the effectiveness of our categorization approach using two real-world document collections from the MEDLINE database. Next, we investigate the application of automatic categorization to text retrieval. Our experiments clearly indicate that automatic categorization improves the retrieval performance compared with no categorization. We also demonstrate that the retrieval performance using automatic categorization achieves the same retrieval quality as the performance using manual categorization. Furthermore, detailed analysis of the retrieval performance on each individual test query is provided     

A comparative study on text representation schemes in text categorization

It is well known that the classification effectiveness of the text categorization system is not simply a matter of learning algorithms. Text representation factors are also at work. This paper will consider the ways in which the effectiveness of text classifiers is linked to the five text representation factors: “stop words removal”, “word stemming”, “indexing”, “weighting”, and “normalization”. Statistical analyses of experimental results show that performing “normalization” can always promote effectiveness of text classifiers significantly. The effects of the other factors are not as great as expected. Contradictory to common sense, a simple binary indexing method can sometimes be helpful for text categorization.     

Material text, immaterial text, and the electronic environment

Digital modes of editing ask us to re-examine the past centuryof editorial theory and to situate emerging editorial approacheswithin this history. Using the computer as a new textual mediumhas brought about a renewed interest in the conditions for representation.This article concerns itself with how books and computers, respectively,represent texts, and how critical editing mediates or organizesthose representations. It was written in 1997 as a criticalresponse to J.J. McGann's essay ‘The Rationale of Hypertext’.     

基于文字混合特征的视频文本定位研究

针对视频中文本信息在视频序列和视频索引中的重要性,本文提出了一种基于文字混合特征的文本定位算法.该算法首先对视频序列中每隔25帧的单帧图像进行边缘检测和投影处理来提取文本块,然后用支持向量基进行筛选,排除非文本块的干扰,最后利用视频序列中相邻帧之间的相关性来搜索剩余帧中的文本块.本文的算法在提高检测速度的同时保证了较高的检测准确度.     

一种基于反向文本频率互信息的文本挖掘算法研究

针对传统的文本分类算法存在着各特征词对分类结果的影响相同,分类准确率较低,同时造成了算法时间复杂度的增加,在分析了文本分类系统的一般模型,以及在应用了互信息量的特征提取方法提取特征项的基础上,提出一种基于反向文本频率互信息熵文本分类算法。该算法首先采用基于向量空间模型(vector spacemodel,VSM)对文本样本向量进行特征提取;然后对文本信息提取关键词集,筛选文本中的关键词,采用互信息来表示并计算词汇与文档分类相关度;最后计算关键词在文档中的权重。实验结果表明了提出的改进算法与传统的分类算法相比,具有较高的运算速度和较强的非线性映射能力,在收敛速度和准确程度上也有更好的分类效果。     

基于边界可信度相似的快速文本分类方法

类别的中心和边界是类别的重要特征.利用训练样本的中心和边界作为分类准则,提出了一种基于边界可信度相似的快速文本分类算法。通过类别边界可信度调整文本与类别的相似性,克服了数据集类别间样本分布不均衡和类别中样本密度不均的缺点,提高了分类性能。实验结果表明该算法提高了文本分类的效果,显示出了较好的鲁棒性,并显著提高了文本分类效率。     

Tables in text

Tables were inserted into a four page article, and subjects were asked to scan the text which was printed in a two-column or a single-column format. The single-column format was scanned significantly faster than the double-column layout, and there were marked reader preferences for the single-column layout.