A Survey on Machine Learning-Based Mobile Big Data Analysis: Challenges and Applications

Author:

Xie Jiyang1ORCID,Song Zeyu1,Li Yupeng2,Zhang Yanting3,Yu Hong1,Zhan Jinnan2,Ma Zhanyu1ORCID,Qiao Yuanyuan3,Zhang Jianhua2ORCID,Guo Jun1

Affiliation:

1. Pattern Recognition and Intelligent Systems Lab., Beijing University of Posts and Telecommunications, Beijing, China

2. State Key Lab. of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China

3. Center for Data Science, Beijing University of Posts and Telecommunications, Beijing, China

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.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

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