Information Retrieval

Instructor:  Prof. Panagiotis Bozanis
Teaching Hours and Credit Allocation:   30 Hours, 6 Credits
Course Assessment:  Exam & Coursework


The course covers the basic principles and techniques of information retrieval, which is the process by which a computer system can respond to a query about a given topic. A successful and meaningful response requires efficient data organization and classification, as well as efficient indexing and clustering algorithms. The students will study all aspects of data organization and processing that allow for efficient information retrieval as well as the underlying computational models and tools.

Learning Outcomes

On completing the course, users will be able to:

  • Understand key concepts of information retrieval techniques and be able to apply these concepts into practice.
  • Apply information retrieval principles to locate relevant information in large collections of data.
  • Understand and deploy efficient techniques for the indexing of document objects that are to be retrieved.
  • Implement features of retrieval systems for web-based and other search tasks.
  • Analyse the performance of retrieval systems.


  • Introduction to information retrieval.
  • Retrieval Models.
  • Dictionaries, term vocabulary and postings lists.
  • Index construction and compression.
  • Vector space model and classification.
  • Support vector machines and machine learning on documents.
  • Search systems.
  • Latent semantic indexing.
  • Link analysis.
  • Evaluation.


  • C.D. Manning, P. Raghavan and H. Schütze (2008), Introduction to Information Retrieval, Cambridge University Press.
  • S. Büttcher, C.L. A. Clarke and G.V. Cormack (20016), Information Retrieval, Implementing and Evaluating Search Engines, MIT Press.
  • Grossman, D.A., Frieder, O. (2004), Information Retrieval, Algorithms and Heuristics, Springer.