雜志介紹

Big Data雜志介紹

《Big Data》是一本以English為(wei)主的(de)(de)(de)未開(kai)放獲取國際優秀(xiu)期(qi)刊(kan)，中文名(ming)稱大數(shu)據，本刊(kan)主要出版(ban)、報(bao)道計算機科學(xue)-COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS領(ling)域(yu)的(de)(de)(de)研究動態以及(ji)在該領(ling)域(yu)取得的(de)(de)(de)各方面的(de)(de)(de)經驗(yan)和(he)科研成果，介(jie)紹該領(ling)域(yu)有關(guan)本專業的(de)(de)(de)最新進展(zhan)，探討行業發(fa)展(zhan)的(de)(de)(de)思路和(he)方法，以促進學(xue)術信息交流，提高行業發(fa)展(zhan)。該刊(kan)已(yi)被國際權威數(shu)據庫SCIE收(shou)錄，為(wei)該領(ling)域(yu)相(xiang)關(guan)學(xue)科的(de)(de)(de)發(fa)展(zhan)起到了(le)良好的(de)(de)(de)推動作用，也得到了(le)本專業人員的(de)(de)(de)廣泛認(ren)可(ke)。該刊(kan)最新影響(xiang)因子為(wei)2.6，最新CiteScore 指(zhi)數(shu)為(wei)9.1。

本刊近期中國學者發表的(de)論文主(zhu)要有：

• Indirect Category Data Transfer Learning Algorithm using Regularization Discrimination

  Author: Liu, Gang; Li, Xiaofeng; Liu, Wangyang

• Bayesian Method for Water Quality Emergency Monitoring in Environmental Pollution Accident Disposal

  Author: Ren, Jia; Wang, Xu; Li, Guangfu

• An Unsupervised Feature Extraction Approach Based on Self-Expression

  Author: Qu, Hongchun; Zheng, Yangqi; Li, Lin; Guo, Fei

• Identification of Potential Cooperation Relationships Among Scientists

  Author: Nian, Fuzhong; Qian, Yinuo; Yao, Yabing

英文介紹

Big Data雜志英文介紹

Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions.

Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government.

Big Data coverage includes:

Big data industry standards,

New technologies being developed specifically for big data,

Data acquisition, cleaning, distribution, and best practices,

Data protection, privacy, and policy,

Business interests from research to product,

The changing role of business intelligence,

Visualization and design principles of big data infrastructures,

Physical interfaces and robotics,

Social networking advantages for Facebook, Twitter, Amazon, Google, etc,

Opportunities around big data and how companies can harness it to their advantage.