Open AccessIdentifying Users Based on Time-Frequency Characteristics
Author(s) -
Yaqiong Gao,
Wanghu Chen,
Yang Bo,
Yuxiang Mu,
Li Jing
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1302/4/042035
Subject(s) - identification (biology) , computer science , similarity (geometry) , behavioral pattern , data mining , world wide web , information retrieval , artificial intelligence , botany , software engineering , image (mathematics) , biology
With the rapid development of information technology, whether it is with regard to the personalized recommendation of the business or network warning by the public security organ, the identification of online users is a very important research topic. The user’s web browsing behavior data contains potential behavioral characteristics, in this paper, we utilize the time-frequency analysis method, which extracts the behavior characteristics when users accessing the network, so as to obtain the user behavior pattern and calculate the similarity between the behavior patterns for achieving the purpose of user identification. This method is verified by the weblog, and the experiment results show that the method extracts user network behavior features based on time-frequency analysis to ensure the accuracy of user identification.