Information Retrieval - Spring 2019

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Overview:

This course provides the basics of information systems from the perspective of the user. The main focus is on relational databases, including tabular data, the relational algebra, the SQL query language, schema design, normal forms, physical architecture, indices. The course also covers support for data cubes on top of relational databases. 

Lecture

Friday, 9:00 to 11:00 in CAB G 11
Exercise

Friday, 11:00 to 12:00 in one of the following:
CAB G 11 - Surnames starting with A-
CAB G 52 - Surnames starting with - 
LFW B3 - Surnames starting with - 
ML J34.1 - Surnames starting with S-Z

 

 

  

Objective

We keep accumulating data at an unprecedented pace, much faster than we can process it. While Big Data techniques contribute solutions accounting for structured or semi-structured shapes such as tables, trees, graphs and cubes, the study of unstructured data is a field of its own: Information Retrieval.

After this course, you will have in-depth understanding of broadly established techniques in order to model, index and query unstructured data (aka, text), including the vector space model, boolean queries, terms, posting lists, dealing with errors and imprecision.

You will know how to make queries faster and how to make queries work on very large datasets. You will be capable of evaluating the quality of an information retrieval engine.

 

Literature

C. D. Manning, P. Raghavan, H. Schütze, Introduction to Information Retrieval, Cambridge University Press.

Prerequisites / Notice

Prior knowledge in elementary set theory, logics, linear algebra, data structures, abstract data types, algorithms, and probability theory (at the Bachelor's level) is required, as well as programming skills (we will use Python).

Piazza

We will use Piazza as the oficial forum for questions.
You can sign up here.
Please post your questions here instead of sending e-mails.