Information Retrieval

Level: Master
Semester: 1st Semester (September - December)
Language: English
Teacher: Jan Hidders
Assistant(s): Jonathan Riggio
Course Description

Retrieving relevant information is one of the central activities in modern knowledge-driven societies. As the amount and variety of data increase at an unprecedented rate, access to relevant, possibly unstructured information is becoming more and more challenging. The World Wide Web is now the primary source of information for leisure and work activities. The real value of the Web can only be unlocked if the huge amount of available data can be found, analysed, and exploited so that each user can quickly find information that is both relevant and comprehensive for their needs.

Information Retrieval (IR) is the discipline that deals with the representation, storage, organisation of, and access to information items, and it is concerned with providing efficient access to large amounts of unstructured contents, such as text, images, videos et cetera. The objective of this course is to introduce the scientific underpinnings of the field of Information Retrieval. The course aims at providing students basic information retrieval concepts and more advanced techniques for efficient data processing, storage, and querying. Students are also provided with a rich and comprehensive catalogue of information search tools that can be exploited in the design and implementation of Web and Enterprise search engines.

The following topics are covered:

  • Basic IR Models (boolean, vector-based, probabilistic); Basic Indexing Techniques; Term Weighting and Scoring;
  • Web Search;
  • Relevance Feedback and Query Expansion;
  • Semantic Search
  • Information Seeking Paradigms
  • Evaluation of information retrieval systems