|
|
|
Naveed Hussain, Hamid Turab Mirza, Ghulam Rasool, Ibrar Hussain and Mohammad Kaleem
Online reviews about the purchase of products or services provided have become the main source of users? opinions. In order to gain profit or fame, usually spam reviews are written to promote or demote a few target products or services. This practice is ...
ver más
|
|
|
|
|
|
|
Xuanyu Zhang, Hao Zhou, Ke Yu, Xiaofei Wu and Anis Yazidi
In Natural Language Processing (NLP), deep-learning neural networks have superior performance but pose transparency and explainability barriers, due to their black box nature, and, thus, there is lack of trustworthiness. On the other hand, classical mach...
ver más
|
|
|
|
|
|
|
Zhi-Yuan Zeng, Jyun-Jie Lin, Mu-Sheng Chen, Meng-Hui Chen, Yan-Qi Lan and Jun-Lin Liu
Consumers? purchase behavior increasingly relies on online reviews. Accordingly, there are more and more deceptive reviews which are harmful to customers. Existing methods to detect spam reviews mainly take the problem as a general text classification ta...
ver más
|
|
|
|
|
|
|
Simon Nam Thanh Vu, Mads Stege, Peter Issam El-Habr, Jesper Bang and Nicola Dragoni
Botnets, groups of malware-infected hosts controlled by malicious actors, have gained prominence in an era of pervasive computing and the Internet of Things. Botnets have shown a capacity to perform substantial damage through distributed denial-of-servic...
ver más
|
|
|
|
|
|
|
Ashokkumar Palanivinayagam, Claude Ziad El-Bayeh and Robertas Dama?evicius
Machine-learning-based text classification is one of the leading research areas and has a wide range of applications, which include spam detection, hate speech identification, reviews, rating summarization, sentiment analysis, and topic modelling. Widely...
ver más
|
|
|
|