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Abstract: LAAW – Linguistic Authorship Analysis of the Dark Web Each year thousands of Canadians, and millions of people worldwide, fall victim to a variety of crimes such as human trafficking, terrorism, gun violence, and cyber-attacks. While these crimes may seem unrelated, they can be traced back to the dark web. The dark web has become a hub for nefarious criminal behaviours such as terrorism, hacking services, and drug and arms sales. Recent evidence demonstrates that criminal networks are complex, and domains do not operate in isolation. Previous findings explore the funding...

MSc Thesis Title: Comparative Study of Deep Learning Models for Sentiment Analysis   Abstract: The rapid expansion of online applications like social media apps and e-commerce websites has led to a large volume of reviews about different subjects, products, and services. Sentiment analysis, which is a crucial area of study in natural language processing, aims to classify the sentiments of these reviews so that the feedback can...

Abstract: Leveraging Dynamics of Feature Space for Effective Semi-supervised Learning with Scarce Data This study introduces a novel semi-supervised learning approach focused on analyzing feature space transformations of a classifier during training and on examining how feature space evolution influences classifier development. The idea is to treat embeddings as moving through the feature space, using their displacement vectors to infer class identities. This concept of “drift of embeddings” allows automatic labeling of new data samples, reducing the need...