数字图书馆科学表型分类

Seongchan Kim, Keejun Han, Soon Young Kim, Ying Liu
{"title":"数字图书馆科学表型分类","authors":"Seongchan Kim, Keejun Han, Soon Young Kim, Ying Liu","doi":"10.1145/2361354.2361384","DOIUrl":null,"url":null,"abstract":"Tables are ubiquitous in digital libraries and on the Web, utilized to satisfy various types of data delivery and document formatting goals. For example, tables are widely used to present experimental results or statistical data in a condensed fashion in scientific documents. Identifying and organizing tables of different types is an absolutely necessary task for better table understanding, and data sharing and reusing. This paper has a three-fold contribution: 1) We propose Introduction, Methods, Results, and Discussion (IMRAD)-based table functional classification for scientific documents; 2) A fine-grained table taxonomy is introduced based on an extensive observation and investigation of tables in digital libraries; and 3) We investigate table characteristics and classify tables automatically based on the defined taxonomy. The preliminary experimental results show that our table taxonomy with salient features can significantly improve scientific table classification performance.","PeriodicalId":91385,"journal":{"name":"Proceedings of the ACM Symposium on Document Engineering. ACM Symposium on Document Engineering","volume":"28 1","pages":"133-136"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Scientific table type classification in digital library\",\"authors\":\"Seongchan Kim, Keejun Han, Soon Young Kim, Ying Liu\",\"doi\":\"10.1145/2361354.2361384\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Tables are ubiquitous in digital libraries and on the Web, utilized to satisfy various types of data delivery and document formatting goals. For example, tables are widely used to present experimental results or statistical data in a condensed fashion in scientific documents. Identifying and organizing tables of different types is an absolutely necessary task for better table understanding, and data sharing and reusing. This paper has a three-fold contribution: 1) We propose Introduction, Methods, Results, and Discussion (IMRAD)-based table functional classification for scientific documents; 2) A fine-grained table taxonomy is introduced based on an extensive observation and investigation of tables in digital libraries; and 3) We investigate table characteristics and classify tables automatically based on the defined taxonomy. The preliminary experimental results show that our table taxonomy with salient features can significantly improve scientific table classification performance.\",\"PeriodicalId\":91385,\"journal\":{\"name\":\"Proceedings of the ACM Symposium on Document Engineering. ACM Symposium on Document Engineering\",\"volume\":\"28 1\",\"pages\":\"133-136\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ACM Symposium on Document Engineering. ACM Symposium on Document Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2361354.2361384\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ACM Symposium on Document Engineering. ACM Symposium on Document Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2361354.2361384","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

摘要

表在数字图书馆和Web上无处不在,用于满足各种类型的数据传递和文档格式化目标。例如,在科学文献中,表格被广泛用于以浓缩的方式呈现实验结果或统计数据。识别和组织不同类型的表对于更好地理解表以及数据共享和重用是绝对必要的任务。本文有三个方面的贡献:1)提出了基于IMRAD (Introduction, Methods, Results, and Discussion)的科学文献表功能分类;2)基于对数字图书馆中表的广泛观察和调查,提出了一种细粒度表分类法;3)研究表的特征,根据已定义的分类法对表进行自动分类。初步实验结果表明,基于显著特征的表分类方法可以显著提高科学表分类的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Scientific table type classification in digital library
Tables are ubiquitous in digital libraries and on the Web, utilized to satisfy various types of data delivery and document formatting goals. For example, tables are widely used to present experimental results or statistical data in a condensed fashion in scientific documents. Identifying and organizing tables of different types is an absolutely necessary task for better table understanding, and data sharing and reusing. This paper has a three-fold contribution: 1) We propose Introduction, Methods, Results, and Discussion (IMRAD)-based table functional classification for scientific documents; 2) A fine-grained table taxonomy is introduced based on an extensive observation and investigation of tables in digital libraries; and 3) We investigate table characteristics and classify tables automatically based on the defined taxonomy. The preliminary experimental results show that our table taxonomy with salient features can significantly improve scientific table classification performance.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
The Notarial Archives, Valletta: Starting from Zero Truncation: all the news that fits we'll print Classifying and ranking search engine results as potential sources of plagiarism An ensemble approach for text document clustering using Wikipedia concepts Document changes: modeling, detection, storage and visualization (DChanges 2014)
×
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