Automatic derivation of context descriptions

Christian Jung, Denis Feth, Yehia Elrakaiby
{"title":"Automatic derivation of context descriptions","authors":"Christian Jung, Denis Feth, Yehia Elrakaiby","doi":"10.1109/COGSIMA.2015.7108177","DOIUrl":null,"url":null,"abstract":"Context-awareness in mobile information systems bears a huge potential. However, context-awareness is still in its infancy and its full potential is not yet exploited. One reason is the poorly supported creation and learning of suitable context descriptions. Another problem is the questionable predictive power of context descriptions that makes it difficult to correctly determine the current user context. For applications that depend on the user context, the reliable determination of the context is essential. In this paper, we propose a process to characterize contexts. We correlate raw contextual information with user activities to determine accurate context descriptions. In a case study, we show how different statistical methods can be used to determine correlations, and analyze their applicability.","PeriodicalId":373467,"journal":{"name":"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COGSIMA.2015.7108177","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Context-awareness in mobile information systems bears a huge potential. However, context-awareness is still in its infancy and its full potential is not yet exploited. One reason is the poorly supported creation and learning of suitable context descriptions. Another problem is the questionable predictive power of context descriptions that makes it difficult to correctly determine the current user context. For applications that depend on the user context, the reliable determination of the context is essential. In this paper, we propose a process to characterize contexts. We correlate raw contextual information with user activities to determine accurate context descriptions. In a case study, we show how different statistical methods can be used to determine correlations, and analyze their applicability.
上下文描述的自动派生
上下文感知在移动信息系统中具有巨大的潜力。然而,上下文感知仍处于起步阶段,其全部潜力尚未得到开发。一个原因是缺乏对创建和学习合适的上下文描述的支持。另一个问题是上下文描述的预测能力存在问题,这使得正确确定当前用户上下文变得困难。对于依赖于用户上下文的应用程序,可靠地确定上下文是必不可少的。在本文中,我们提出了一个表征上下文的过程。我们将原始上下文信息与用户活动关联起来,以确定准确的上下文描述。在一个案例研究中,我们展示了如何使用不同的统计方法来确定相关性,并分析它们的适用性。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信