Wires DMKD的目標(biāo)是：（a）通過主要研究人員正在進(jìn)行的一系列評論來展示當(dāng)前數(shù)據(jù)挖掘和知識發(fā)現(xiàn)的技術(shù)現(xiàn)狀；（b）通過包括從數(shù)據(jù)挖掘和K的不同角度討論關(guān)鍵主題的文章來捕獲該領(lǐng)域的關(guān)鍵跨學(xué)科風(fēng)格。知識發(fā)現(xiàn)，包括技術(shù)、商業(yè)、醫(yī)療保健、教育、政府、社會(huì)和文化領(lǐng)域的各種應(yīng)用領(lǐng)域，（c）通過內(nèi)容更新的系統(tǒng)程序捕獲數(shù)據(jù)挖掘和知識發(fā)現(xiàn)的快速發(fā)展，（d）通過展示其成就鼓勵(lì)積極參與這一領(lǐng)域。以一種方便的方式向廣大觀眾提出挑戰(zhàn)。期刊的內(nèi)容將有助于高層次的本科生和研究生、學(xué)術(shù)項(xiàng)目的教學(xué)和研究教授以及工業(yè)領(lǐng)域的科學(xué)家和研究管理者。數(shù)據(jù)挖掘和知識發(fā)現(xiàn)（DMKD）技術(shù)目前正應(yīng)用于商業(yè)和政府的許多領(lǐng)域，如銀行和金融、市場研究、風(fēng)險(xiǎn)分析和反恐。在科學(xué)領(lǐng)域，DMKD已廣泛應(yīng)用于生物信息學(xué)、醫(yī)學(xué)診斷、流行病學(xué)、藥物發(fā)現(xiàn)、環(huán)境建模和氣象數(shù)據(jù)分析等領(lǐng)域。

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.