Text Mining

3 units

Text mining extracts valuable insights and actionable information from vast amounts of unstructured textual data. It is a rapidly evolving field at the intersection of natural language processing and machine learning, and is applied in various domains including healthcare, social media analysis, financial prediction and beyond. This undergraduate course covers a wide range of text mining approaches, from traditional statistical methods to cutting-edge techniques. Students will gain both in-depth knowledge of fundamental concepts and hands-on experience in practical applications. Topics of the course include text representation learning, text classification, named entity recognition, relation extraction, taxonomy and knowledge graph construction, and retrieval-augmented generation. Through programming assignments and a semester-long project, students will develop hands-on text mining skills necessary for real-world scenarios.