中文简介
Wires DMKD的目标是：（a）通过主要研究人员正在进行的一系列评论来展示当前数据挖掘和知识发现的技术现状；（b）通过包括从数据挖掘和K的不同角度讨论关键主题的文章来捕获该领域的关键跨学科风格。知识发现，包括技术、商业、医疗保健、教育、政府、社会和文化领域的各种应用领域，（c）通过内容更新的系统程序捕获数据挖掘和知识发现的快速发展，（d）通过展示其成就鼓励积极参与这一领域。以一种方便的方式向广大观众提出挑战。期刊的内容将有助于高层次的本科生和研究生、学术项目的教学和研究教授以及工业领域的科学家和研究管理者。数据挖掘和知识发现（DMKD）技术目前正应用于商业和政府的许多领域，如银行和金融、市场研究、风险分析和反恐。在科学领域，DMKD已广泛应用于生物信息学、医学诊断、流行病学、药物发现、环境建模和气象数据分析等领域。
英文简介
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.
近年期刊自引率趋势图
JCR分区
| JCR分区等级 | JCR所属学科 | 分区 | 影响因子 |
| Q1 | COMPUTER SCIENCE, THEORY & METHODS | Q1 | 7.558 |
| COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Q1 |
近年期刊影响因子趋势图
CiteScore数值
| CiteScore | SJR | SNIP | 学科类别 | 分区 | 排名 | 百分位 |
| 21.00 | 2.901 | 5.662 | 大类：Computer Science 小类：General Computer Science | Q1 | 5 / 231 |
98% |
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