Knowledge models from PDF textbooks

IF 1.4 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS New Review of Hypermedia and Multimedia Pub Date : 2021-02-28 DOI:10.1080/13614568.2021.1889692
Isaac Alpizar Chacon, Sergey Sosnovsky
{"title":"Knowledge models from PDF textbooks","authors":"Isaac Alpizar Chacon, Sergey Sosnovsky","doi":"10.1080/13614568.2021.1889692","DOIUrl":null,"url":null,"abstract":"ABSTRACT Textbooks are educational documents created, structured and formatted by domain experts with the primary purpose to explain the knowledge in the domain to a novice. Authors use their understanding of the domain when structuring and formatting the content of a textbook to facilitate this explanation. As a result, the formatting and structural elements of textbooks carry the elements of domain knowledge implicitly encoded by their authors. Our paper presents an extensible approach towards automated extraction of knowledge models from textbooks and enrichment of their content with additional links (both internal and external). The textbooks themselves essentially become hypertext documents where individual pages are annotated with important concepts in the domain. The evaluation experiments examine several aspects and stages of the approach, including the accuracy of model extraction, the pragmatic quality of extracted models using one of their possible applications— semantic linking of textbooks in the same domain, the accuracy of linking models to external knowledge sources and the effect of integration of multiple textbooks from the same domain. The results indicate high accuracy of model extraction on symbolic, syntactic and structural levels across textbooks and domains, and demonstrate the added value of the extracted models on the semantic level.","PeriodicalId":54386,"journal":{"name":"New Review of Hypermedia and Multimedia","volume":"27 1","pages":"128 - 176"},"PeriodicalIF":1.4000,"publicationDate":"2021-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/13614568.2021.1889692","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"New Review of Hypermedia and Multimedia","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1080/13614568.2021.1889692","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 10

Abstract

ABSTRACT Textbooks are educational documents created, structured and formatted by domain experts with the primary purpose to explain the knowledge in the domain to a novice. Authors use their understanding of the domain when structuring and formatting the content of a textbook to facilitate this explanation. As a result, the formatting and structural elements of textbooks carry the elements of domain knowledge implicitly encoded by their authors. Our paper presents an extensible approach towards automated extraction of knowledge models from textbooks and enrichment of their content with additional links (both internal and external). The textbooks themselves essentially become hypertext documents where individual pages are annotated with important concepts in the domain. The evaluation experiments examine several aspects and stages of the approach, including the accuracy of model extraction, the pragmatic quality of extracted models using one of their possible applications— semantic linking of textbooks in the same domain, the accuracy of linking models to external knowledge sources and the effect of integration of multiple textbooks from the same domain. The results indicate high accuracy of model extraction on symbolic, syntactic and structural levels across textbooks and domains, and demonstrate the added value of the extracted models on the semantic level.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
PDF教材中的知识模型
教科书是由领域专家创建、组织和格式化的教育文档,主要目的是向新手解释该领域的知识。作者在构建和格式化教科书内容时使用他们对领域的理解来促进这种解释。因此,教科书的格式和结构元素携带了作者隐式编码的领域知识元素。我们的论文提出了一种可扩展的方法,用于从教科书中自动提取知识模型,并通过额外的链接(内部和外部)丰富其内容。教科书本身本质上变成了超文本文档,其中各个页面都用该领域的重要概念进行了注释。评估实验考察了该方法的几个方面和阶段,包括模型提取的准确性,使用其可能的应用之一(同一领域教科书的语义链接)提取的模型的语用质量,将模型链接到外部知识来源的准确性以及来自同一领域的多本教科书的集成效果。结果表明,在跨教科书和跨领域的符号、句法和结构层面上,模型提取具有较高的准确性,并展示了提取模型在语义层面上的附加价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
New Review of Hypermedia and Multimedia
New Review of Hypermedia and Multimedia COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
3.40
自引率
0.00%
发文量
4
审稿时长
>12 weeks
期刊介绍: The New Review of Hypermedia and Multimedia (NRHM) is an interdisciplinary journal providing a focus for research covering practical and theoretical developments in hypermedia, hypertext, and interactive multimedia.
期刊最新文献
Geo-spatial hypertext in virtual reality: mapping and navigating global news event spaces User-centred collecting for emerging formats The evolution of the author—authorship and speculative worldbuilding in Johannes Heldén’s Evolution From “screen-as-writing” theory to Internet culturology. A French perspective on digital textualities Pasifika arts Aotearoa and Wikipedia
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1