Research on Analysis and Recognition of Car User Portrait based on Big Data of Vehicle Network

Authors

  • Jinxi Pang
  • Jin Lu

DOI:

https://doi.org/10.62051/ijcsit.v5n2.13

Keywords:

Big Data of the Internet of Vehicles, User Portrait Recognition, Data Preprocessing, Feature Extraction, Model Construction

Abstract

With the rapid development of vehicle networking technology, big data of vehicle networking has become one of the core resources of intelligent transportation system. As the key technology of the application of big data in the networking of vehicles, the analysis and identification of user portraits play an important role in realizing the landing of user portraits and precise advertising, improving the efficiency of traffic management, ensuring driving safety and optimizing the user experience. This paper aims to explore the research on user portrait analysis and recognition based on vehicle network big data, and realize the accurate identification of user portrait through comprehensive analysis of vehicle driving data, user behavior characteristics and other information. First of all, the basic data fields of the big data of the Internet of vehicles are introduced, and then the data is structured, including data preprocessing, feature extraction, feature recombination, and finally the unsupervised model K-Means++ is used for model construction. Through experimental verification, the method proposed in this paper has achieved good results in the recognition and analysis of user portrait, and can realize the landing of user portrait and precise advertisement delivery scene, which has high practical application value.

Downloads

Download data is not yet available.

References

[1] Wang Lan. User identity recognition based on IPTV big data research [D]. South China university of technology, 2020. DOI: 10.27151/d.cnki.ghnlu.2020.004976.

[2] LI Shuangshuang. Research on Identity Identification Technology Based on Online Traffic Characteristics of Mobile Users [D]. Huazhong University of Science and Technology, 2015.

[3] Xu Neng. Across social network user identity recognition algorithm research [D]. Anhui architecture university, 2022. DOI: 10.27784/d.cnki.gahjz.2022.000373.

[4] TIAN Hengyi, WANG Yu, XIAO Hongbing. Automatic brain tumor segmentation algorithm based on multi-modal feature recombination and scale cross attention mechanism [J]. Chinese Journal of Lasers, 2024, 51 (21): 129-138.

[5] Zhang Fan, Guo Yaxin, Yang Jing, et al. Research on electric energy prediction based on GBDT+ feature engineering method [J]. Electronic Quality, 2020, (01): 1-4.

[6] FANG Xiao, YUAN Xiaofang, Guan Donglin, et al. Research on Abnormal User Behavior Detection based on K-means Algorithm [J]. Network Security Technology and Application, 2025, (02): 23-25.

[7] HAN Xiaocui, Hu Yewei, Wu Qingyan, et al. Abnormal data recognition and automatic processing system of personnel management based on K-means clustering algorithm [J]. Electronic Design Engineering, 2024, 32 (24): 27-31. DOI:10.14022/ j. ssn1674-6236.2024.24.006.

[8] Chen Hongtao. Correlation Analysis of Student Behavior Data and Academic Achievement based on K-means Algorithm [J]. China Science and Technology Information, 2024, (23): 86-88.]

Downloads

Published

27-02-2025

Issue

Section

Articles

How to Cite

Pang, J., & Lu, J. (2025). Research on Analysis and Recognition of Car User Portrait based on Big Data of Vehicle Network. International Journal of Computer Science and Information Technology, 5(2), 104-110. https://doi.org/10.62051/ijcsit.v5n2.13