首页    期刊浏览 2024年11月28日 星期四
登录注册

文章基本信息

  • 标题:Mining Big Data in Real Time
  • 本地全文:下载
  • 作者:Albert Bifet
  • 期刊名称:Informatica
  • 印刷版ISSN:1514-8327
  • 电子版ISSN:1854-3871
  • 出版年度:2013
  • 卷号:37
  • 期号:1
  • 出版社:The Slovene Society Informatika, Ljubljana
  • 摘要:Streaming data analysis in real time is becoming the fastest and most efficient way to obtain useful knowl- edge from what is happening now, allowing organizations to react quickly when problems appear or to detect new trends helping to improve their performance. Evolving data streams are contributing to the growth of data created over the last few years. We are creating the same quantity of data every two days, as we created from the dawn of time up until 2003. Evolving data streams methods are becoming a low-cost, green methodology for real time online prediction and analysis. We discuss the current and future trends of mining evolving data streams, and the challenges that the field will have to overcome during the next years.
  • 关键词:big data; data streams; data mining
国家哲学社会科学文献中心版权所有