中文簡介

Wires DMKD的目標是：（a）通過主要研究人員正在進行的一系列評論來展示當前數據挖掘和知識發現的技術現狀；（b）通過包括從數據挖掘和K的不同角度討論關鍵主題的文章來捕獲該領域的關鍵跨學科風格。知識發現，包括技術、商業、醫療保健、教育、政府、社會和文化領域的各種應用領域，（c）通過內容更新的系統程序捕獲數據挖掘和知識發現的快速發展，（d）通過展示其成就鼓勵積極參與這一領域。以一種方便的方式向廣大觀眾提出挑戰。期刊的內容將有助于高層次的本科生和研究生、學術項目的教學和研究教授以及工業領域的科學家和研究管理者。數據挖掘和知識發現（DMKD）技術目前正應用于商業和政府的許多領域，如銀行和金融、市場研究、風險分析和反恐。在科學領域，DMKD已廣泛應用于生物信息學、醫學診斷、流行病學、藥物發現、環境建模和氣象數據分析等領域。

　　英文簡介

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.

　　近年期刊自引率趨勢圖

　　JCR分區

JCR分區等級	JCR所屬學科	分區	影響因子
Q1	COMPUTER SCIENCE, THEORY & METHODS	Q1	7.558
	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	Q1

　　近年期刊影響因子趨勢圖

　　CiteScore數值

CiteScore	SJR	SNIP	學科類別	分區	排名	百分位
21.00	2.901	5.662	大類：Computer Science 小類：General Computer Science	Q1	5 / 231	98%

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