Principles of Information Retrieval

Área Científica do Menor 6.0 ECTS 1st Cycle Studies

Year
0

Academic year
2026-2027

Code
01013735

Subject Area
Área Científica do Menor

Language of Instruction
Portuguese

Mode of Delivery
Face-to-face

Duration
SEMESTRIAL

ECTS Credits
6.0

Type
Elective

Level
1st Cycle Studies

Recommended Prerequisites

N.A.

Teaching Methods

The curricular unit takes the form of theoretical and practical classes, supplemented by application exercises. The topics will also be explored in working groups. The final grade is the sum of the following elements: problem-solving exercises, test and research paper.

Learning Outcomes

At the end of the course, students should be able to demonstrate: (i) an understanding of the concepts, theories and models of information retrieval (ii) skills in planning and developing effective search strategies for information retrieval, (iii) the skills needed to critically evaluate the capabilities and limitations of information retrieval systems and models, and (iv) the ability to identify, analyse and discuss current issues and research, as well as future developments in information retrieval.

Work Placement(s)

Syllabus

1. General concepts of the principles and theories of information retrieval
2. The structure of databases and controlled vocabulary searches
3. Effective search strategies
4. Selecting databases and repositories
5. Other information retrieval tools
6. Current issues and research

Head Lecturer(s)

Maria Manuel Lopes de Figueiredo Costa Marques Borges

Assessment Methods

Assessment
Resolution Problems: 20.0%
Mini Tests: 40.0%
Research work: 40.0%

Bibliography

Hambarde, K., & Proença, H. (2023). Information Retrieval: Recent Advances and Beyond. IEEE Access, 11, 76581-76604. https://doi.org/10.1109/access.2023.3295776.
Li, H., & Balinas, E. S. (2025). The Impact of Generative Artificial Intelligence on University Information Literacy Education: A Systematic Review from Challenges to Changes. International Journal of Latest Technology in Engineering Management & Applied Science, 14(2), 25-38. https://doi.org/10.51583/IJLTEMAS.2025.1402004
Ortega, J.-L. (2024). El devenir de las bases de datos académicas y sus diferentes paradigmas. Anuario ThinkEPI, 18. https://doi.org/10.3145/thinkepi.2024.e18a03
Shah, C., & Bender, E. (2024). Envisioning Information Access Systems: What Makes for Good Tools and a Healthy Web?. ACM Transactions on the Web, 18, 1 - 24. https://doi.org/10.1145/3649468.
White, R. W., & Shah, C. (Eds.). (2025). Information Access in the Era of Generative AI (Vol. 51). Springer Nature. https://doi.org/10.1007/978-3-031-73147-1.