*恭喜浙江省农业科学院俞老师在SCI期刊 Environmental Science and Pollution Research(IF:2.914)上成功发表
*恭喜西安理工大学张老师,环境水利专业,文章成功发表在SCI期刊Environmental Science and Pollution Research上,IF2.914
*恭喜山东交通学院谢老师在SCI期刊APPLIED SURFACE SCIENCE(IF5.15)上成功发表
*恭喜华中科技大学黄老师在SCI期刊 ACS Applied Materials & Interfaces(IF8.456)上成功发表
*恭喜中南大学湘雅医院黄医生在Frontiers in Oncology(IF 4.137)上成功发表
*恭喜复旦大学辛博士在SCI期刊 FEBS LETTERS(IF2.675)上成功发表
*恭喜中南大学陈博士在THIN-WALLED STRUCTURESSCI期刊(IF3.488)上成功发表
*恭喜湖南工学院郭老师在SCI期刊SIMULATION MODELLING PRACTICE AND THEORY(IF2.42)上成功发表
*恭喜东华大学闫老师在SCI期刊Advanced Functional Materials(IF 15.621)上成功发表
*恭喜安徽医科大学肖老师在SCI期刊BMC CELL BIOLOGY(IF 3.485)上成功发表
*恭喜四川大学华西医院谢医生在SCI期刊European Heart Journal: Acute Cardiovascular Care(IF 3.734)上成功发表

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2021年最新SCI期刊影响因子查询系统

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Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery 期刊详细信息

基本信息
期刊名称 Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery
期刊ISSN 1942-4787
期刊官方网站 http://onlinelibrary.wiley.com/journal/10.1002/%28ISSN%291942-4795
是否OA
出版商 John Wiley and Sons Inc.
出版周期
始发年份
年文章数 40
最新影响因子 7.558(2021)
中科院SCI期刊分区
大类学科 小类学科 Top 综述
工程技术3区 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机:人工智能4区
COMPUTER SCIENCE, THEORY & METHODS 计算机:理论方法3区
CiteScore
CiteScore排名 CiteScore SJR SNIP
学科 排名 百分位 5.23 0.928 2.593
Computer Science
General Computer Science
8 / 204 96%
补充信息
自引率 8.50%
H-index 22
SCI收录状况 Science Citation Index Expanded
官方审稿时间
网友分享审稿时间 数据统计中,敬请期待。
PubMed Central (PML) http://www.ncbi.nlm.nih.gov/nlmcatalog?term=1942-4787%5BISSN%5D
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收稿范围
The objectives of WIREs DMKD are to (a) present the current state of the art of data mining and knowledge discovery through an ongoing series of reviews written by leading researchers, (b) capture the crucial interdisciplinary flavor of the field by including articles that address the key topics from the differing perspectives of data mining and knowledge discovery, including a variety of application areas in technology, business, healthcare, education, government and society and culture, (c) capture the rapid development of data mining and knowledge discovery through a systematic program of content updates, and (d) encourage active participation in this field by presenting its achievements and challenges in an accessible way to a broad audience. The content of WIREs DMKD will be useful to upper-level undergraduate and postgraduate students, to teaching and research professors in academic programs, and to scientists and research managers in industry.
The techniques of data mining and knowledge discovery (DMKD) are now being applied in many areas of business and government, such as banking and finance, market research, risk analysis, and counterterrorism. In the sciences, DMKD has become pervasive in such fields as bioinformatics, medical diagnosis, epidemiology, drug discovery, environmental modeling, and meteorological data analysis.
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