泛在人工智能和动态数据流

A. Bifet, J. Read
{"title":"泛在人工智能和动态数据流","authors":"A. Bifet, J. Read","doi":"10.1145/3210284.3214345","DOIUrl":null,"url":null,"abstract":"Artificial Intelligence is leading to ubiquitous sources of Big Data arriving at high-velocity and in real-time. To effectively deal with it, we need to be able to adapt to changes in the distribution of the data being produced, and we need to do it using a minimum amount of time and memory. In this paper, we detail modern applications falling into this context, and discuss some state-of-the-art methodologies in mining data streams in real-time, and the open source tools that are available to do machine learning/data mining in real-time for this challenging setting.","PeriodicalId":412438,"journal":{"name":"Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Ubiquitous Artificial Intelligence and Dynamic Data Streams\",\"authors\":\"A. Bifet, J. Read\",\"doi\":\"10.1145/3210284.3214345\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Artificial Intelligence is leading to ubiquitous sources of Big Data arriving at high-velocity and in real-time. To effectively deal with it, we need to be able to adapt to changes in the distribution of the data being produced, and we need to do it using a minimum amount of time and memory. In this paper, we detail modern applications falling into this context, and discuss some state-of-the-art methodologies in mining data streams in real-time, and the open source tools that are available to do machine learning/data mining in real-time for this challenging setting.\",\"PeriodicalId\":412438,\"journal\":{\"name\":\"Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3210284.3214345\",\"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 12th ACM International Conference on Distributed and Event-based Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3210284.3214345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

人工智能正在导致无处不在的大数据来源以高速和实时的方式到来。为了有效地处理它,我们需要能够适应正在生成的数据分布的变化,并且我们需要使用最少的时间和内存来做到这一点。在本文中,我们详细介绍了在这种背景下的现代应用,并讨论了实时挖掘数据流的一些最先进的方法,以及可用于在这种具有挑战性的环境中进行实时机器学习/数据挖掘的开源工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ubiquitous Artificial Intelligence and Dynamic Data Streams
Artificial Intelligence is leading to ubiquitous sources of Big Data arriving at high-velocity and in real-time. To effectively deal with it, we need to be able to adapt to changes in the distribution of the data being produced, and we need to do it using a minimum amount of time and memory. In this paper, we detail modern applications falling into this context, and discuss some state-of-the-art methodologies in mining data streams in real-time, and the open source tools that are available to do machine learning/data mining in real-time for this challenging setting.
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
×
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