Information Retrieval and Web Search (IE663 + IE691)

Course Schedule

Lecture 01: Introduction to Information Retrieval (Mar 1)

Lecture 02: Boolean Retrieval and Term Indexing (Mar 8)

Lecture 03: Data Structures in IR and Tolerant Retrieval (Mar 15)

Lecture 04: Term Weighting and Vector Space Model  (Mar 22)

Exercises 01: Covers L1-L3 (Mar 22)

Easter break: Mar 29 & Apr 5

Lecture 05: Probabilistic IR (Apr 12)

Lecture 06: Language Modeling for IR (Apr 19)

Lecture 07: Relevance Feedback and Query Expansion (Apr 26)

Exercise 02: Covers L4-L6 (Apr 26)

Lecture 08: Latent and Semantic Information Retrieval Models (May 3)

Lecture 09: Classification, Clustering, Learning to Rank (May 10)

Lecture 10: Neural Information Retrieval (May 19)

Exercise 03: Covers L7-L9 (May 19)

Lecture 11: IR Evaluation & Link Analysis (May 31)

Lecture 12: Cross-Lingual Retrieval (June 7)

Exercise 04: Covers L10-L12 (June 7)

General description

Level: Master (Diploma)


  • Fundamental notions of linear algebra, probability theory, as well as algorithms and data structures
  • Programming skills (a higher-level pgoramming languages like Java, Python, C#, or C++ recommended) for the IR Project (IE 681)


Given the vastness and richness of the Web, users need high-performing, scalable and efficient methods to access its wealth of information and satisfy their information needs. As such, being able to search and effectively retrieve relevant pieces of information from large text collections is a crucial task for the majority (if practically not all) of Web applications. In this course we will explore a variety of basic and advanced techniques for text-based information retrieval and Web search. Coursework will include exercises, and a final exam (IE 663). Homework assignments are meant to introduce the students to the problems that will be covered in the final exam.

For the IR project course, IE 691,  students are expected to successfully complete a team project in teams of 3 people. The projects will focus on a variety of IR problems covered in class. Project deliverables include both software (i.e., code and documentation) and a short report explaining the work performed and its evaluation.


Teaching staff:


  • On Mondays, starting at 13.45 (approximately 1.5 hours lecture session)
  • Exercise sessions and project sessions start at 15.30
  • Zoom room: WIM-ZOOM-04 (Zoom link visible in Portal2 and ILIAS)

Course materials:

  • Include lecture slides and exercise/homework assignment sheets.
  • All materials will be posted in the ILIAS page of the course


C. D. Manning, P. Raghavan and H. Schütze, Introduction to Information Retrieval, Cambridge University Press, 2008 (available at

B. Croft, D. Metzler, T. Strohman, Search Engines: Information Retrieval in Practice, Addison-Wesley, 2009 (available at

R. Baeza-Yates, B. Ribeiro-Neto, Modern Information Retrieval, Addison-Wesley, 2011 (2nd Edition).