Wiley Interdisciplinary Reviews-data Mining And Knowledge Discovery

Wiley Interdisciplinary Reviews-data Mining And Knowledge Discovery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.

Wiley Interdisciplinary Reviews-data Mining And Knowledge Discovery中文簡介

《Wiley Interdisciplinary Reviews-data Mining And Knowledge Discovery》是一本由John Wiley and Sons Inc.出版商出版的專業(yè)工程技術(shù)期刊，該刊創(chuàng)刊于2011年，刊期6 issues/year，該刊已被國際權(quán)威數(shù)據(jù)庫SCIE收錄。在中科院最新升級版分區(qū)表中，該刊分區(qū)信息為大類學(xué)科：計算機(jī)科學(xué) 2區(qū)，小類學(xué)科：計算機(jī)：理論方法 2區(qū)；計算機(jī)：人工智能 3區(qū)；在JCR（Journal Citation Reports）分區(qū)等級為Q1。該刊發(fā)文范圍涵蓋計算機(jī)：人工智能等領(lǐng)域，旨在及時、準(zhǔn)確、全面地報道國內(nèi)外計算機(jī)：人工智能工作者在該領(lǐng)域取得的最新研究成果、工作進(jìn)展及學(xué)術(shù)動態(tài)、技術(shù)革新等，促進(jìn)學(xué)術(shù)交流，鼓勵學(xué)術(shù)創(chuàng)新。2021年影響因子為7.558，平均審稿速度>12周，或約稿。

中科院分區(qū)最新升級版（當(dāng)前數(shù)據(jù)版本：2021年12月最新升級版）

大類學(xué)科	分區(qū)	小類學(xué)科	分區(qū)	Top期刊	綜述期刊
計算機(jī)科學(xué)	2區(qū)	COMPUTER SCIENCE, THEORY & METHODS 計算機(jī)：理論方法 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 計算機(jī)：人工智能	2區(qū) 3區(qū)	否	是

JCR分區(qū)（當(dāng)前數(shù)據(jù)版本：2021-2022年最新版）

JCR分區(qū)等級	JCR所屬學(xué)科	分區(qū)	影響因子
Q1	COMPUTER SCIENCE, THEORY & METHODS	Q1	7.558
	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	Q1

期刊指數(shù)

影響因子	h-index	Gold OA文章占比	研究類文章占比	OA開放訪問	平均審稿速度
7.558	31	8.33%	27.50%	未開放	>12周，或約稿

IF值(影響因子)趨勢圖