In e-commerce, user reviews can play a significant role in determining the revenue of an
organisation. Online users rely on reviews before making decisions about any product and …

In the fraud graph, fraudsters often interact with a large number of benign entities to hide
themselves. So, there are not only the homophilic connections formed by the same label …

Fraud detection is one of the most important tasks in Web platforms such as e-commerce,
social media, network security, and financial systems. To prevent fraudulent actions from …

Machine learning has been widely applied to building security applications. However, many
machine learning models require the continuous supply of representative labeled data for …

Online reviews significantly impact consumers who are purchasing or seeking services via
the Internet. Businesses and review platforms need to manage these online reviews to avoid …

The proliferation of attacks on On-line Social Networks (OSNs) has imposed particular
attention by providers and users. This has an even higher importance for Social Reviewing …

Online Social Media (OSM) platforms such as Twitter, Facebook are extensively exploited by
the users of these platforms for spreading the (mis) information to a large audience …

The increasingly developed online platform generates a large amount of online reviews
every moment, eg, Yelp and Amazon. Consumers gradually develop the habit of reading …

Customers use reviews as a primary source of information to judge a product or service.
Positive reviews help boost companies' reputations, increasing their revenue by attracting …

Graph Neural Network has been proved to be effective for fraud detection for its capability to
encode node interaction and aggregate features in a holistic view. Recently, Transformer …