协助基于内容的文档标记和分类

K. Wrona, S. Oudkerk, A. Armando, Silvio Ranise, Riccardo Traverso, Lisa Ferrari, Richard McEvoy
{"title":"协助基于内容的文档标记和分类","authors":"K. Wrona, S. Oudkerk, A. Armando, Silvio Ranise, Riccardo Traverso, Lisa Ferrari, Richard McEvoy","doi":"10.1109/ICMCIS.2016.7496589","DOIUrl":null,"url":null,"abstract":"The correct labelling of all information at its point of origin is a critical enabler for effective information access control in modern military systems. If information is not properly labeled it cannot be shared between different communities of interest and coalition partners, which affects the responsibility to share and potentially impedes ongoing military operations. This paper describes two experiments performed at the NATO Communications and Information Agency related to supporting correct labelling of both pre-existing and newly created information objects. Two different techniques are used, one based on semantic analysis and the other on machine learning. Both approaches offer promising results in their respective use case scenarios, but require further development prior to operational deployment.","PeriodicalId":103155,"journal":{"name":"2016 International Conference on Military Communications and Information Systems (ICMCIS)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Assisted content-based labelling and classification of documents\",\"authors\":\"K. Wrona, S. Oudkerk, A. Armando, Silvio Ranise, Riccardo Traverso, Lisa Ferrari, Richard McEvoy\",\"doi\":\"10.1109/ICMCIS.2016.7496589\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The correct labelling of all information at its point of origin is a critical enabler for effective information access control in modern military systems. If information is not properly labeled it cannot be shared between different communities of interest and coalition partners, which affects the responsibility to share and potentially impedes ongoing military operations. This paper describes two experiments performed at the NATO Communications and Information Agency related to supporting correct labelling of both pre-existing and newly created information objects. Two different techniques are used, one based on semantic analysis and the other on machine learning. Both approaches offer promising results in their respective use case scenarios, but require further development prior to operational deployment.\",\"PeriodicalId\":103155,\"journal\":{\"name\":\"2016 International Conference on Military Communications and Information Systems (ICMCIS)\",\"volume\":\"66 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Military Communications and Information Systems (ICMCIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMCIS.2016.7496589\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Military Communications and Information Systems (ICMCIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMCIS.2016.7496589","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

在现代军事系统中,对所有信息的来源进行正确标记是有效的信息访问控制的关键因素。如果信息没有正确标记,就不能在不同的利益团体和联盟伙伴之间共享,这会影响共享的责任,并可能阻碍正在进行的军事行动。本文描述了在北约通信和信息局进行的两项实验,这些实验与支持对已有和新创建的信息对象进行正确标记有关。使用了两种不同的技术,一种基于语义分析,另一种基于机器学习。这两种方法在各自的用例场景中都提供了有希望的结果,但是在操作部署之前需要进一步的开发。
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
Assisted content-based labelling and classification of documents
The correct labelling of all information at its point of origin is a critical enabler for effective information access control in modern military systems. If information is not properly labeled it cannot be shared between different communities of interest and coalition partners, which affects the responsibility to share and potentially impedes ongoing military operations. This paper describes two experiments performed at the NATO Communications and Information Agency related to supporting correct labelling of both pre-existing and newly created information objects. Two different techniques are used, one based on semantic analysis and the other on machine learning. Both approaches offer promising results in their respective use case scenarios, but require further development prior to operational deployment.
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
Delay analysis of STDMA in grid wireless sensor networks Assisted content-based labelling and classification of documents Assessing NATO policy alignment through text analysis: An initial study Learning multi-channel power allocation against smart jammer in cognitive radio networks A novel OFDM sensing method based on CAF-max for hybrid detectors architecture
×
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