Pattern mining for query answering in marine sensor data

Md. Sumon Shahriar, Paulo A. de Souza, G. Timms
{"title":"Pattern mining for query answering in marine sensor data","authors":"Md. Sumon Shahriar, Paulo A. de Souza, G. Timms","doi":"10.1109/ICDIM.2011.6093319","DOIUrl":null,"url":null,"abstract":"An integrated pattern mining technique for query answering is proposed for marine sensor data. In pattern query, we adopt the dynamic time warping (DTW) method and propose the use of a query relaxation approach in finding similar patterns. We further calculate prediction from discovered similar patterns in marine sensor data. The predictive values are then compared with the forecast from hydrodynamic model data. In addition, we present query answering using a clustering technique. Finally, we show implementation results in a marine sensor network deployed in the South East of Tasmania, Australia.","PeriodicalId":355775,"journal":{"name":"2011 Sixth International Conference on Digital Information Management","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Sixth International Conference on Digital Information Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDIM.2011.6093319","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

An integrated pattern mining technique for query answering is proposed for marine sensor data. In pattern query, we adopt the dynamic time warping (DTW) method and propose the use of a query relaxation approach in finding similar patterns. We further calculate prediction from discovered similar patterns in marine sensor data. The predictive values are then compared with the forecast from hydrodynamic model data. In addition, we present query answering using a clustering technique. Finally, we show implementation results in a marine sensor network deployed in the South East of Tasmania, Australia.
船舶传感器数据查询应答的模式挖掘
提出了一种用于海洋传感器数据查询应答的集成模式挖掘技术。在模式查询中,我们采用动态时间规整(DTW)方法,并提出使用查询松弛方法来查找相似的模式。我们从海洋传感器数据中发现的类似模式进一步计算预测。然后将预测值与水动力模型数据的预测值进行比较。此外,我们提出了使用聚类技术的查询回答。最后,我们展示了部署在澳大利亚塔斯马尼亚州东南部的海洋传感器网络的实施结果。
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