Information Retrieval and Web Search (FSS2017)

News

First lecture

Tomorrow, Tuesday 14.2.2017. we will have our first lecture of the course, "Introduction to Information Retrieval". The lecture will start at 8.30 in the building A5, lecture room C013. You can find the slides for the lecture on ILIAS.

We put the start of the course on the Valentine's day so you fall in love with this course! 

________________________________________________________________________________________________

General description

Level: Master (Diploma)

Prerequisites:  

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

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 Tuesdays, starting at 8.30 am (1.5 hours lecture session, followed by an exercise session)

Office hours: Every Friday at 14.30, B6 26, Building C, Room C1.02 (please previously inform us via email when you plan to come)

Lectures period:

  • First lecture: February 14, 2017
  • Last lecture (project presentations): May 30
  • Easter break (no lectures): April 11 and April 18

Course materials: Include lecture slides and exercise/homework assignment sheets. All materials will be posted on this page as well as on the ILIAS page of this course, at least one week in advance (i.e., one week before the corresponding lecture). 

Lecture schedule

  • Lecture 01 (Feb 14): Introduction to Information Retrieval
  • Lecture 02 (Feb 21): Boolean Retrieval and Term Indexing
  • Lecture 03 (Feb 28): Data Structures in IR and Tolerant Retrieval
  • Lecture 04 (Mar 7): Term Weighting and Vector Space Model
  • Lecture 05 (Mar 14): Probabilistic Information Retrieval
  • Lecture 06 (Mar 21): Language Modelling for Information Retrieval
  • Lecture 07 (Mar 28): Relevance Feedback and Query Expansion
  • Lecture 08 (Apr 4): Latent and Semantic Information Retrieval Models
  • Lecture 09 (May 9): Classification, Clustering, and Learning to Rank
  • Lecture 10 (Apr 25): Evaluation of Information Retrieval Systems 
  • Lecture 11 (May 2): Web Search and Link Analysis
  • Lecture 12 (May 16): Distributed Information Retrieval
  • Lecture 13 (May 23): Student projects coaching
  • Lecture 14 (May 30): Student project presentations

Grading / Evaluation

●     50% final exam

●     50% final project

NOTE: you need a pass grade in both the exam and the project to get an overall pass for this course!

Final Exam. Coursework will include homework assignments: these are meant to give you a reasonable idea of the topics and exercises that will be covered in the final exam at the end of the course. Students are required to submit at least 4 out of 5 assignments and get 50% of available points.

Final Project. Students are expected to successfully complete a term project in teams of 2-3 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 (about 5-10 pages) explaining the work and evaluation.

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).