Titlebook: Security and Privacy in Communication Networks; 19th EAI Internation Haixin Duan,Mourad Debbabi,Man Ho Allen Au Conference proceedings 2025

entice

Magnitude

Xin Zong,Min Luo,Cong Peng,Debiao Hecenarios, it suffers heavy computational cost because it examines distances between each points multiple times, especially in traffic applications which usually require calculating road network shortest distance instead of Euclidean distance. Therefore, the performance of DBSCAN for real-time cluste

小卒

Yue Huang,Yongyan Guo,Cheng Huangmon to see data collection with the unbalanced spatial distribution. For example, some cities may release check-ins for multiple years while others only release a few days of data. In this paper, we tackle the problem of successive POI recommendation for the cities with only a short period of data s

縮短

侵略主義

彎腰

Handedness

天然熱噴泉

Yanru Xiao,Cong Wang,Xing Gaoor large scale graphs is trained by full-batch stochastic gradient descent, which causes two problems: over-smoothing and neighborhood expansion, which may lead to loss of model accuracy and high memory and computational overhead. To alleviate these two challenges, we propose CDGCN, a novel GCN algo

使人煩燥

Botao Xu,Haizhou Wang the problems of data imbalance and lack of data labels, it is a great challenge to build ship behavior analysis and anomaly detection models based on trajectory data. Based on transfer learning and Transformer architecture, this paper proposes an anomaly detection method for adaptive Transformer mo

強(qiáng)制令