A Survey on Machine Learning-Based Mobile Big Data Analysis: Challenges and Applications. (1st August 2018)

• Record Type: Journal Article
• Authors: Xie, Jiyang; Song, Zeyu; Li, Yupeng; Zhang, Yanting; Yu, Hong; Zhan, Jinnan; Ma, Zhanyu; Qiao, Yuanyuan; Zhang, Jianhua; Guo, Jun
• Other Names: Liu Liu Academic Editor.
• Is Part Of: Wireless communications and mobile computing. Volume 2018(2018)
• Publication Date: 2018-08-01
• Subjects: Wireless communication systems -- Periodicals; Mobile communication systems -- Periodicals; 621.38205
• DOI: 10.1155/2018/8738613
• Languages: English
• ISSNs: 1530-8669

Abstract

Abstract : This paper attempts to identify the requirement and the development of machine learning-based mobile big data (MBD) analysis through discussing the insights of challenges in the mobile big data. Furthermore, it reviews the state-of-the-art applications of data analysis in the area of MBD. Firstly, we introduce the development of MBD. Secondly, the frequently applied data analysis methods are reviewed. Three typical applications of MBD analysis, namely, wireless channel modeling, human online and offline behavior analysis, and speech recognition in the Internet of Vehicles, are introduced, respectively. Finally, we summarize the main challenges and future development directions of mobile big data analysis.