期刊文献+

《Big Data Mining and Analytics》

作品数195被引量223H指数7
Big data are datasets whose size is beyond the ability of commonly used algorithms and computing sys...查看详情>>
  • 主办单位清华大学
  • 国际标准连续出版物号2096-0654
  • 国内统一连续出版物号10-1514/G2
  • 出版周期季刊

期刊信息

  • 主管单位教育部
  • 主办单位清华大学
  • 总编/主编潘毅;郑纬民
  • 地址北京市海淀区双清路雪岩大厦B608C
  • 邮政编码100084
  • 电话010-83470494
  • 单价200
  • 定价800

期刊简介

Big data are datasets whose size is beyond the ability of commonly used algorithms and computing systems to capture, manage, and process the data within a reasonable time.Big Data Mining and Analytics discovers hidden patterns, correlations, insights and knowledge through mining and analyzing large amounts of data obtained from various applications.Big data come from many applications such as social media, sensors, Internet of Things, scientific applications, surveillance, video and image archives. With today’s technology in storage and computing and many newly invented statistical methods, data mining and machine learning algorithms such as deep learning, it is possible to analyze data and get good answers from them quickly.Big Data Mining and Analytics addresses the most innovative developments, research issues and solutions in big data research and their applications.

获奖情况

  • CCF计算领域高质量期刊2022

收录情况

  • 美国·Web of Science数据库(2020)
  • 荷兰·Scopus数据库(2020)
  • 中国·中国人文社科核心期刊
  • 英国·科学文摘数据库
  • 美国·工程索引
  • 瑞典·开放获取期刊指南
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