@Article{jiot.2020.09868,
AUTHOR = {Rui Li, Guang Sun, Jingyi He, Ying Jiang, Rui Sun, Haixia Li, Peng Guo, Jianjun Zhang},
TITLE = {Gender Forecast Based on the Information about People Who Violated  Traffic Principle},
JOURNAL = {Journal on Internet of Things},
VOLUME = {2},
YEAR = {2020},
NUMBER = {2},
PAGES = {65--73},
URL = {http://www.techscience.com/jiot/v2n2/40131},
ISSN = {2579-0080},
ABSTRACT = {User portrait has been a booming concept in big data industry in 
recent years which is a direct way to restore users’ information. When it talks 
about user portrait, it will be connected with precise marketing and operating. 
However, there are more ways which can reflect the good use of user portrait.
Commercial use is the most acceptable use but it also can be used in different 
industries widely. The goal of this paper is forecasting gender by user portrait 
and making it useful in transportation safety. It can extract the information from 
people who violated traffic principle to know the features of them then forecast 
the gender of these people. Finally, it will analyze the prediction based on 
characteristics correlation and forecasting results from models which can verify 
if gender can have an obvious influence on the traffic violation. Also we hope 
give some advice to drivers and traffic department by doing this research.},
DOI = {10.32604/jiot.2020.09868}
}