Foto: Anna Logue

Information Retrieval and Web Search

Course Schedule

This is the schedule for modules IE 663 (Information Retrieval and Web Search) and IE 691/681 (Information Retrieval Project) for FSS 2020. 

Monday, Feb 17: 

   - 13.45: Lecture 01: Introduction to Information Retrieval

   - 15.30: IR Project: Topics Presentation

Monday, Feb 24: 

   - 13.45: Lecture 02: Boolean Retrieval and Inverted Index

Monday, Mar 2: 

   - 13.45: Lecture 03: Data Structures in IR and Tolerant Retrieval

   - 15.30: IR Project coaching (optional, email announcement)

Monday, Mar 9: 

   - 13.45: Lecture 04:  Term Weighting and Vector Space Model

   - 15.30: Exercise session #1: Boolean retrieval, inverted index, tolerant retrieval

Monday, Mar 16: 

   - 13.45: Lecture 05: Probabilistic Information Retrieval

   - 15:30: Lecture 06: Language Modelling for Information Retrieval

Monday, Mar 23: 

   - 13.45: Lecture 07: Relevance Feedback and Query Expansion

   - 15.30: Exercise session #2: VSM, Probabilistic and LM Retrieval

Monday, Mar 30: 

   - 13.45: Lecture 08: Latent and Semantic Retrieval

   - 15.30: IR Project coaching (optional, email announcement)

Apr 6 & 13: Easter Break 

Monday, Apr 20: 

   - 13.45: Lecture 09: Classification, Clustering, Learning to Rank,

                Lecture 10: Evaluation

   - 15.30: Exercise session #3: Relevance feedback, Semantic retrieval

Monday, April 27: 

   - 13.45: Lecture 11: Web Search and Link Analysis

   - 15.30: Exercise session #4: Classification, L2R, Evaluation, Web Search

Monday, May 4: 

   - 15.30: IR Project final coaching (optional, announcement)

Monday, May 18: 

   - 13.45: IR Project presentations

Friday, June 5: 

   - Exam


General description

Level: Master (Diploma)

Prerequisites:  

  • 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)

Description:

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 homework assignments (exercises), a term project and a final exam. Homework assignments are meant to introduce the students to the problems that will be covered in the final exam. In addition, students are expected to successfully complete a term project in teams of 2-4 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.

Organization

Teaching staff:

Lectures:

  • On Mondays, starting at 13.45 am (approximately 1.5 hours lecture session)

Office hours:

  • Goran: Fridays in lecture weeks at 10.00, B6 26, Building C, Room C1.02 (previous announcement via email)
  • Robert: Thursday in lecture weeks at 15.00, B6 26, Building C, Room C1.05 (previous announcement via email)

Course materials:

  • Include lecture slides and exercise/homework assignment sheets.
  • All materials will be posted in the ILIAS page of the course; lectures are also linked on this site

Textbooks

C. D. Manning, P. Raghavan and H. Schütze, Introduction to Information Retrieval, Cambridge University Press, 2008 (available at http://nlp.stanford.edu/IR-book).

B. Croft, D. Metzler, T. Strohman, Search Engines: Information Retrieval in Practice, Addison-Wesley, 2009 (available at  http://ciir.cs.umass.edu/irbook/).

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