Master of Science in Data Science and Artificial Intelligence 

Winter Semester 2024

Information retrieval focuses on accessing and extracting information from various document collections. This course explores key concepts and methods in information retrieval, with an emphasis on practical applications in web-based environments.

Given that text-based information retrieval often relies on natural language processing (NLP), the course also covers essential NLP techniques. Students will gain hands-on experience by building NLP pipelines and developing custom-trained machine learning models for real-world information retrieval tasks

Learning Outcomes

• Information Retrieval system architectures
• Implementing NLP pipelines
• Web information extraction
• Performing link analysis in web graphs
• Implementing recommender systems

Topics

•  Introduction. Boolean retrieval model.
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References

Introduction to Information Retrieval, C. D. Manning, P. Raghavan, H. Schuetze, Cambridge University Press, 2008

To be updated..