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Information Retrieval and Web Search (FSS2018)

Course Schedule

Feb 11: Lecture 01: Introduction to Information Retrieval

Feb 18: Lecture 02: Boolean Retrieval and Inverted Index

Feb 25: Lecture 03:  Data Structures in IR and Tolerant Retrieval

Mar 4: Lecture 04:  Term Weighting and Vector Space Model

Mar 11: No lecture

Mar 18: Lecture 05: Probabilistic Information Retrieval

Mar 25: Lecture 06: Language Modelling for Information Retrieval

Apr 1: Lecture 07: Relevance Feedback and Query Expansion

Apr 8: IR Project coaching (IE 681), no lecture

Apr 15: Easter break, no lecture

Apr 22: Easter break, no lecture

Apr 29: Lecture 08: Latent and Semantic Retrieval

May 6: Lecture 09: Classification, Clustering, Learning to Rank, Evaluation

May 13: IR Project coaching (IE 681), no lecture

May 20: Lecture 10: Web Search and Link Analysis

May 27: IR Project presentations (IE 681), no lecture


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 15.00, 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)

Lectures period:

  • First lecture session: February 11, 2018
  • Last lecture session: May 20, 2019
  • No sessions: March 11, April 8, April 15, April 22, May 13 (Easter break, Project coaching sessions)

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).