The upsurge in the volume of unwanted emails called spam has created an intense need for
the development of more dependable and robust antispam filters. Machine learning …

Text mining in big data analytics is emerging as a powerful tool for harnessing the power of
unstructured textual data by analyzing it to extract new knowledge and to identify significant …

Text classification is fundamental in natural language processing (NLP), and Graph Neural
Networks (GNN) are recently applied in this task. However, the existing graph-based works …

Abstract Machine learning models are known to lack robustness against inputs crafted by an
adversary. Such adversarial examples can, for instance, be derived from regular inputs by …

The popularity of short message service (SMS) has been growing over the last decade. For
businesses, these text messages are more effective than even emails. This is because while …

The collaborative Internet of Things (C-IoT) is an emerging paradigm that involves many
communities with the idea of cooperating in data gathering and service sharing. Many fields …

The problem of classification has been widely studied in the data mining, machine learning,
database, and information retrieval communities with applications in a number of diverse …

Text mining has found a variety of applications in diverse domains. Of late, prolific work is
reported in using text mining techniques to solve problems in financial domain. The …

Email spam is a serious problem that annoys recipients and wastes their time. Machine-
learning methods have been prevalent in spam detection systems owing to their efficiency in …

Machine learning systems offer unparalled flexibility in dealing with evolving input in a
variety of applications, such as intrusion detection systems and spam e-mail filtering …