Frontiers In Big Data

杂志介绍

Frontiers In Big Data杂志介绍

《Frontiers In Big Data》是一本以English为主的未开放获取国际优秀期刊，中文名称大数据前沿，本刊主要出版、报道计算机科学-计算机信息系统领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCIE收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为3.8，最新CiteScore 指数为7.3。

本刊近期中国学者发表的论文主要有：

• A reinforcement learning-guided interpretable method for postoperative sepsis prediction with Hilbert-Schmidt Independence Criterio

  Author: Zhong, Kunhua; Chen, Han; Sun, Qilong; Wang, Peng; Liu, Zhenbei; Chen, Yuwen

• A disease potential-driven graph attention model for comorbidity risk prediction of hypertensio

  Author: Zhou, Leming; Qin, Hanshu; Yang, Yanmei; Huang, Gang; Liu, Zhigang

• Jingdezhen ceramic culture in the digital era: a qualitative inquiry into digital dissemination and platform innovatio

  Author: Huang, Qiuyang; Chen, Zhengjun

• GFTrans: an on-the-fly static analysis framework for code performance profilin

  Author: Li, Jie; Wen, Yunbao; Liu, Jingxin; Zeng, Biqing; Mirjalili, Seyedali

英文介绍

Frontiers In Big Data杂志英文介绍

Frontiers In Big Data is a professional journal focusing on the latest advances and applications in the field of big data. Its content covers a number of frontier areas of big data technology, including big data networks, big data applications in high-energy physics, the combination of artificial intelligence and big data, network security and privacy protection. These areas involve not only data storage and processing technologies, but also how big data can be used to improve decision-making and solve practical problems.

In terms of big data networks, the journal discusses network architecture, data transmission technologies, and efficiency improvements in data processing. The application of big data in high energy physics explores how to analyze complex experimental data through efficient data processing techniques to advance scientific research. The journal also focuses on the combination of big data and artificial intelligence, especially in how machine learning algorithms process and analyze massive amounts of data to enable intelligent decisions.