| 期刊ISSN: | 1942-4787 |
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| E-ISSN: | 1942-4795 |
| 影响因子: | 6.4 |
| 自引率: | 1.6% |
| 检索数据库: | |
| 出版语言: | 英文 |
| 期刊分类: |
| 最新中科院SCI期刊分区(基础版) | |
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大学学科
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计算机技术
二区
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计算机:人工智能
二区
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Top期刊
否
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综述期刊
是
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| 最新中科院SCI期刊分区(升级版) | |
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大学学科
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按学科分区
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Top期刊
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综述期刊
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| 出版信息 | |
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| 出版商 |
John Wiley and Sons Inc.
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| 期刊官网 | http://onlinelibrary.wiley.com/journal/10.1002/%28ISSN%291942-4795 |
| 涉及的研究方向 |
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, THEORY & METHODS
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| 年文章数 |
0
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| 是否OA |
否
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| APC费用 | |
| SCI期刊收录coverage | |
| 期刊简介 | |
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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.
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| Cite Score相关 | |||
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| Cite Score | SJR | SNIP | 排名 |
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