COS 470: Introduction to Information Retrieval

Course Topics

An introduction to the theories and implementation techniques used in modern search engines. As part of the course, students will develop their own search engines using available information retrieval (IR) toolkits. Topics in the course include user interfaces for information retrieval systems, search result evaluation, text processing including natural language processing, retrieval models (e.g., Boolean, vector space, probabilistic, and learning-based methods such as neural information retrieval), and ethical dilemmas regarding the use of IR systems in society.

Course Materials

• Search Engines: Information Retrieval in Practice (Bruce Croft, Donald Metzler, and Trevor Strohman; University of Massachussets at Amherst)
• Introduction to Information Retrieval (Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze; Stanford University, University of Stuttgart, and the University of Munich)

Learning Outcomes

• Describe the different information retrieval models, and to compare their weaknesses and strengths
• Analyze the performance of an Information Retrieval system by applying the proper evaluation measures
• Design and implement real applications using Information Retrieval systems
• Apply clustering and classification techniques to a corpus of texts for a specific information need
• Understand and apply neural information retrieval models on real-world data

Lectures

Assignment

Projects