Supervisor

• Malte Josten, M.Sc.

Thesis: Bachelor’s/Master’s Thesis

This thesis compares the effectiveness of different text representation techniques, i.e., single words, chargrams, n-grams, or sentence embeddings, for spam and phishing detection. The goal is to identify the differences, weaknesses, and strengths for each method and compare them.

Prerequisities

Required

• Basic understanding of machine learning and articifial intelligence (finished the course Foundations of Artificial Intelligence)
• Familiarity with Natural Language Processing techniques, e.g., text classification and feature extraction techniques
• Proficiency in at least one programming language (preferably Python)

Optional

• You took the following courses:
  • Internettechnologies & Web Engineering
  • Advanced Methods of Machine Learning
  • Security in Communication Networks
• Familiarity with evaluation metrics for AI models
• Proficiency in using LaTeX