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《Big Data》杂志封面
  • 所属分类:首页 > SCI期刊 > 工程技术
  • 期刊名: Big Data
  • 期刊名缩写:BIG DATA-US
  • 期刊ISSN:N/A
  • E-ISSN:2167-647X
  • 2025年影响因子/JCR分区:2.0/Q2 查看近年IF趋势图
  • 5年平均影响因子:4.1
  • 学科分类与版本:COMPUTER SCIENCE, THEORY & METHODS - SCIE; COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS - SCIE
  • 出版周期:
  • 出版年份:0
  • 出版国家或地区:UNITED STATES
  • 出版商:MARY ANN LIEBERT, INC
  • 年文章数:查看近年文章发表趋势图
  • 论著文章占比:100.00% [论著 ÷(论著 + 综述)]
  • 是否OA开放访问:No
  • Gold OA文章占比:1.89%
  • 官方网站:www.ibm.com/big-data/us/en/
  • 投稿网址:
  • 编辑部地址:140 HUGUENOT STREET, 3RD FL, NEW ROCHELLE, USA, NY, 10801

《Big Data》中科院JCR分区

  • 2025年3月升级版:
  • 大类小类学科Top综述期刊
    计算机科学 4区
    COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
    计算机:跨学科应用
    4区
    COMPUTER SCIENCE, THEORY & METHODS
    计算机:理论方法
    4区

  • 2023年12月升级版:
  • 大类小类学科Top综述期刊
    计算机科学 4区
    COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
    计算机:跨学科应用
    4区
    COMPUTER SCIENCE, THEORY & METHODS
    计算机:理论方法
    4区

    《Big Data》期刊简介:

    Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions.

    Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government.

    Big Data coverage includes:
    Big data industry standards,
    New technologies being developed specifically for big data,
    Data acquisition, cleaning, distribution, and best practices,
    Data protection, privacy, and policy,
    Business interests from research to product,
    The changing role of business intelligence,
    Visualization and design principles of big data infrastructures,
    Physical interfaces and robotics,
    Social networking advantages for Facebook, Twitter, Amazon, Google, etc,
    Opportunities around big data and how companies can harness it to their advantage.

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    《Big Data》评估说明

      《Big Data》发布于爱科学网,并永久归类相关SCI期刊导航类别中,本站只是硬性分析 "《BIG DATA-US》" 杂志的可信度。学术期刊真正的价值在于它是否能为科技进步及社会发展带来积极促进作用。"《BIG DATA-US》" 的价值还取决于各种因素的综合分析。

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