User Behavior Identification and Personalized Recommendation Based on Web Data Mining

Ya Wang
2021 North atlantic university union: International Journal of Circuits, Systems and Signal Processing  
A good understanding of user behavior and consumption preferences can provide support for website operators to improve their service quality. However, the existing personalized recommendation systems generally have problems such as low Web data mining efficiency, low degree of automated recommendation, and low durability. Targeting at these unsolved issues, this paper mainly carries out the following works: Firstly, the authors established a user behavior identification and personalized
more » ... dation model based on Web data mining, it gave the user behavior analysis process based on Web data mining, improved the traditional k-means algorithm, and gave the detailed execution steps of the improved algorithm; moreover, it also elaborated on the K nearest neighbor model based on user scoring information, the score matrix decomposition method, and the personalized recommendation method for network users. At last, experimental results verified the effectiveness of the constructed model.
doi:10.46300/9106.2021.15.72 fatcat:xgeiknhge5btvfqk2llf7szss4