{"title":"移动设备上的PDF可读性增强","authors":"Zachary Shelton, Chen-Hsiang Yu","doi":"10.1145/3371300.3383352","DOIUrl":null,"url":null,"abstract":"In the past, researchers studied readability enhancement of English articles for non-native English readers, either on paper reading or hypertext reading. Using a variety of methods, researchers were able to enhance the reading comprehension and the users' satisfaction on hypertext reading, such as changing content presentation with visual-syntactic text formatting (VSTF) format or Jenga format. In terms of dynamically changing content presentation for reading, one less explored format is Portable Document Format (PDF), which was traditionally viewed within a modern Web browser or Adobe Acrobat reader on the desktop. PDF format was standardized as an open format in 2008 and has been widely used to keep a fixed-layout content. However, a fixed layout document presents a challenge to apply existing transformation methods, not mention on mobile devices. In this paper, we present a system that uses a novel algorithm to decode a PDF document and apply content transformation to enhance its readability. Although we used Jenga format as an example to enhance the readability of PDF documents, we envision the proposed framework can be used to adopt different transformation methods. The system was implemented in a mobile device and we are able to apply a basic transformation to a PDF document at both the sentence and paragraph levels. The main contribution of this research is we extend previous work of readability enhancement from paper document and hypertext content to PDF documents. Current result is promising, and we believe it is worth further investigation to make PDF documents readable and accessible on the Web for different populations, such as non-native English readers, people with dyslexia or special needs, etc.","PeriodicalId":93137,"journal":{"name":"Proceedings of the 17th International Web for All Conference","volume":"20 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PDF readability enhancement on mobile devices\",\"authors\":\"Zachary Shelton, Chen-Hsiang Yu\",\"doi\":\"10.1145/3371300.3383352\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the past, researchers studied readability enhancement of English articles for non-native English readers, either on paper reading or hypertext reading. 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引用次数: 0
摘要
过去有研究针对非英语为母语的读者进行了提高英语文章可读性的研究,无论是纸质阅读还是超文本阅读。研究者采用多种方法来提高超文本阅读的阅读理解能力和用户满意度,如将内容呈现改为视觉语法文本格式(VSTF)格式或叠叠格式。在动态更改内容表示以供阅读方面,一种较少探索的格式是可移植文档格式(Portable Document format, PDF),它传统上是在现代Web浏览器或桌面上的Adobe Acrobat阅读器中查看的。PDF格式在2008年被标准化为开放格式,并被广泛用于保持固定布局的内容。然而,固定布局文档在应用现有的转换方法时面临挑战,更不用说在移动设备上了。在本文中,我们提出了一个系统,使用一种新颖的算法来解码PDF文档,并应用内容转换来提高其可读性。虽然我们使用Jenga格式作为示例来增强PDF文档的可读性,但我们设想所提出的框架可以用于采用不同的转换方法。该系统是在移动设备上实现的,我们能够在句子和段落级别上对PDF文档进行基本转换。本研究的主要贡献在于将以往的纸质文档和超文本内容的可读性增强工作扩展到PDF文档。目前的结果是有希望的,我们认为值得进一步的研究,使PDF文档在网络上可读和可访问的不同人群,如非英语母语的读者,有阅读障碍或特殊需要的人等。
In the past, researchers studied readability enhancement of English articles for non-native English readers, either on paper reading or hypertext reading. Using a variety of methods, researchers were able to enhance the reading comprehension and the users' satisfaction on hypertext reading, such as changing content presentation with visual-syntactic text formatting (VSTF) format or Jenga format. In terms of dynamically changing content presentation for reading, one less explored format is Portable Document Format (PDF), which was traditionally viewed within a modern Web browser or Adobe Acrobat reader on the desktop. PDF format was standardized as an open format in 2008 and has been widely used to keep a fixed-layout content. However, a fixed layout document presents a challenge to apply existing transformation methods, not mention on mobile devices. In this paper, we present a system that uses a novel algorithm to decode a PDF document and apply content transformation to enhance its readability. Although we used Jenga format as an example to enhance the readability of PDF documents, we envision the proposed framework can be used to adopt different transformation methods. The system was implemented in a mobile device and we are able to apply a basic transformation to a PDF document at both the sentence and paragraph levels. The main contribution of this research is we extend previous work of readability enhancement from paper document and hypertext content to PDF documents. Current result is promising, and we believe it is worth further investigation to make PDF documents readable and accessible on the Web for different populations, such as non-native English readers, people with dyslexia or special needs, etc.