—— 要投稿,上万维,轻松学术交流

严正声明

本站非期刊官网,非中介代理,
不向作者收取任何费用!
举报微信:13140028228 冯老师

态度公正、信息求实、投稿自助、使用免费
大数据挖掘与分析(英文)(Big Data Mining and Analytics)
CN外文 - 双月刊
  • 大数据挖掘与分析(英文)(Big Data Mining and Analytics)
  • 复合影响因子:1.619
  • CSCD(2025-2026)科技核心(2025学术卷)AMI入库(2022)
  • 万方目次,维普目次
  • /有基金 100.0%
  投稿方式:官网投稿
  • 栏目频次
  • 一作占比
  • 单位占比
  • 热词

中频栏目

33.3%期平均发文量7篇
33.3%期平均发文量8篇
33.3%期平均发文量6篇
33.3%期平均发文量1篇
100.0%
暂无单位信息.
暂无关键词信息.
  • 更多

    期刊简介

  • 《大数据挖掘与分析(英文)》(Big Data Mining and Analytics)(双月刊),创刊于2018年,由教育部主管,清华大学主办,清华大学出版社出刊,是一本聚焦大数据前沿发展的国际化专业学术期刊。期刊发表大数据挖掘与分析方面高水平的原创性研究和综述类文章,为国内外大数据研究者提供高端学术交流平台。

  • 基本信息

  • 期刊名称:大数据挖掘与分析(英文)(Big Data Mining and Analytics)
  • 主管单位:教育部
  • 主办单位:清华大学
  • 国内刊号:CN10-1514/G2
  • 国际刊号:ISSN 2096-0654
  • 出刊日期:
    期刊定价:
  • 邮发代码:
  • 所在省区:北京
    邮政编码:
  • 联系地址:

  • 投稿信息

  • 学科分类:自动化|计算机
    版面费用:待核实
  • 字数要求:24000-58000
    查重要求:- ;AIGC检测:-
  • 复合因子:1.619
    综合因子:0.968
  • 审  稿 费:待核实
    稿费:待核实
  • 本刊可发:
  • 特殊属性:

  • 联系方式

  • 投稿网址:https://mc03.manuscriptcentral.com/bdma
  • 官网网址:https://www.sciopen.com/journal/2096-0654
  • 电话传真:010-83470494(官网电话)
  • 电子邮箱:journal-bdma@tup.tsinghua.edu.cn(202503期)
  • 微信公众号:大数据挖掘与分析期刊(bigdatajournal)

审稿时间:暂无参考数据,审稿时间不确定!

投稿难度:网友分享,仅供参考

见刊周期:-

温馨提示以上只是参考信息,实际情况会根据投稿主题、稿件质量和数量、审稿流程有所差异。想获得更准确信息请联系期刊的编辑部进行咨询。

欢迎点评!让信息更透明,使投稿更轻松!
    • 审稿时间:
      是否录用:
    • 发表排期:
      查重要求:
    • 有无课题:
      有无回复:
    • 我的学历:
      我的职称:
    • 审稿费用:
      版面费用:
    • 稿       费:
      稿件字数:
    • 投稿难度:
    • 该刊可发:
    • 投稿主题:
匿名: 验证码: 点击切换验证码
    • 1、投稿方式:在线投稿。

      2、刊内网址(202503期):

      https://www.sciopen.com/journal/2096-0654

      https://ieeexplore.ieee.org/xpl/aboutJournal.jsp?punumber=8254253

      https://mc03.manuscriptcentral.com/bdma(投稿系统)

      3、清华大学出版社期刊中心官网:

      https://www.tsinghuajournals.com/

      4、官网电话:010-83470494

      5、刊内邮箱:journal-bdma@tup.tsinghua.edu.cn

      6、出刊日期:双月刊,逢双月出版。

      7、官方微信公众号:大数据挖掘与分析期刊(bigdatajournal)

      2025年9月4星期四

      《大数据挖掘与分析(英文)》期刊简介

      【官方微信公众号信息】

      大数据挖掘与分析期刊2025年08月07日

      《大数据挖掘与分析(英文)》(Big Data Mining and Analytics,ISSN 2096-0654,CN 10-1514/G2,双月刊)创刊于2018年,为国际化的英文学术期刊,由教育部主管,清华大学主办,清华大学出版社出版。由清华大学教授、中国工程院院士郑纬民和深圳理工大学讲席教授、美国医学与生物工程院院士、俄罗斯工程院院士、乌克兰国家工程院院士、欧洲科学与艺术院院士潘毅共同担任主编。期刊发表大数据挖掘与分析方面高水平的原创性研究和综述类文章,为国内外大数据研究者提供高端学术交流平台。期刊与IEEE合作,以开放获取(OA)模式海外发行。期刊已被ESCI,CSCD,EI,Scopus,dblp computer science bibliography,Google Scholar,INSPEC等检索收录。期刊位居中科院期刊分区计算机科学1区Top期刊。期刊位列CCF计算领域高质量科技期刊分级目录T1类。

      自创刊以来,Big Data Mining and Analytics得到业内专家、学者广泛关注。期刊2024年影响因子6.2,在所属的人工智能、信息系统领域均位居Q1区。根据爱思唯尔最新公布的CiteScore(引用分数),BDMA 2024年CiteScore为19.8,位列全球计算机领域前2%。2024年入选“中国科技期刊卓越行动计划”英文梯队期刊项目。

      Submission Guidelines

      【官网信息】

      Overview

      Big

      Data Mining and Analytics, an academic journal sponsored by Tsinghua

      University, is published quarterly. This journal aims at presenting the

      up-to-date scientific achievements with high creativity and great

      significance in big data mining and analytics. Contributions all over

      the world are welcome. Big Data Mining and Analytics is indexed by IEEE

      Xplore.

      Manuscripts

      are selected for publication according to the editorial assessment of

      their suitability and evaluation from independent reviewers. Papers are

      usually sent to two or more reviewers. Editorial staff will edit

      accepted papers to improve accuracy and clarity and shorten, if

      necessary.

      It

      is a condition of publication that manuscripts submitted to this

      journal have not been published and will not be simultaneously submitted

      or published elsewhere.

      Manuscript submission

      The

      electronic manuscript should be sent to the editorial board through

      ScholarOne Manuscripts at http://mc03.manuscriptcentral.com/bdma.

      Authorship

      Authorship

      should be limited to those who have made a significant contribution to

      the conception, design, execution, or interpretation of the reported

      study. All those who have made significant contributions should be

      listed as co-authors. Where there are others who have participated in

      certain substantive aspects of the research project, they should be

      named in an Acknowledgment section. The corresponding author should

      ensure that all appropriate co-authors (according to the above

      definition) and no inappropriate co-authors are included in the author

      list of the manuscript, and that all co-authors have seen and approved

      the final version of the paper and have agreed to its submission for

      publication. After acceptance, changes of authorship or in the order of

      the authors listed will not be accepted by Tsinghua University Press.

      Title and By-line

      The

      title should be descriptive, not full sentences. Name, affiliation

      (institution) of the authors, city, zip code, country, and E-mail

      address of the author(s) should be listed.

      Abstract and Key words

      The abstract of about 100−150 words must accompany each

      article on page one. It should be a concise summary of the aims,

      methods, results, and conclusions and/or other significant items in the

      paper. Together with the title, it must be adequate as an index to all

      the subjects treated in the paper, and will be used as a base for

      indexing. Abstracts shall not contain numbered mathematical equations

      nor numbered references. If a citation is made, reword the sentence to

      exclude citation numbers. Define all nonstandard symbols and

      abbreviations. Do not use footnote indicators. Summarize the

      experimental or theoretical results, the conclusions, and/or other

      significant items in the paper. If space permits, include any important

      new quantitative data. Summarized results should be exact, direct, and

      specific. The key words should include 3−8 pieces of words or phrases to serve as guidelines for indexing.

      ......

      更多详情:

      https://www.sciopen.com/journal/join_journal/submission_guidelines?id=1404097305465446402&issn=2096-0654

    评分:0

    验证码: 点击切换验证码