Course Description

Objective

The goal of this course is to study the theory and algorithms that support the organization and search of large collections of unstructured data including text, images, sound and video. The initial part of the course covers the basis of text-based information retrieval, the second part is devoted to the particularities and challenges of web search, and the final part reviews current information retrieval research topics.

Methodology

    • Professor's lectures on fundamental topics

    • Practical assignments and exercises to be solved by students

    • Technical papers' review and presentation by students

    • Final project

    • Written and practical tests. Students must show a good grasp of concepts and skills covered in the course.

Contents

Grading

    • Assignments 40%

    • Exams 30%

    • Presentation 15%

    • Final project 15%

References

    • [IIR08] Manning, C. D., Raghavan, P., & Schütze, H. (2008). Introduction to information retrieval. Cambridge: Cambridge University Press. (main textbook)

    • [MIR99] Baeza-Yates, R. A., & Neto, B. R. (1999). Modern information retrieval.

    • [MAN99] Witten, I. H., Moffat, A., & Bell, T. C. (1999). Managing gigabytes: compressing and indexing documents and images. Morgan Kaufmann.

    • [TREC05] Voorhees, E., & Harman, D. K. (Eds.). (2005). TREC: Experiment and evaluation in information retrieval. MIT press.

    • [RR05] Moffat, A., Zobel, J., & Hawking, D. (2005, December). Recommended reading for IR research students. In ACM SIGIR Forum (Vol. 39, No. 2, pp. 3-14). ACM.

Resources