Deep Learning Driven Venue Recommender for Event-Based Social Networks

2020 ◽  
Vol 32 (11) ◽  
pp. 2129-2143 ◽  
Author(s):  
Soumajit Pramanik ◽  
Rajarshi Haldar ◽  
Anand Kumar ◽  
Sayan Pathak ◽  
Bivas Mitra
Author(s):  
Hongzhi Yin ◽  
Lei Zou ◽  
Quoc Viet Hung Nguyen ◽  
Zi Huang ◽  
Xiaofang Zhou

Author(s):  
Putra Wanda ◽  
Marselina Endah Hiswati ◽  
Huang J. Jie

Manual analysis for malicious prediction in Online Social Networks (OSN) is time-consuming and costly. With growing users within the environment, it becomes one of the main obstacles. Deep learning is growing algorithm that gains a big success in computer vision problem. Currently, many research communities have proposed deep learning techniques to automate security tasks, including anomalous detection, malicious link prediction, and intrusion detection in OSN. Notably, this article describes how deep learning makes the OSN security technique more intelligent for detecting malicious activity by establishing a classifier model.


Author(s):  
Hao Ding ◽  
Chenguang Yu ◽  
Guangyu Li ◽  
Yong Liu
Keyword(s):  

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