Kies de Nederlandse taal
Course module: 201600083
Advanced Project in Information Retrieval
Course info
Course module201600083
Credits (ECTS)5
Course typeCourse
Language of instructionEnglish
Contact persondr. S. Wang
prof.dr. T.W.C. Huibers
dr. N. Strisciuglio
Examiner R.B. Trieschnigg
Contactperson for the course
dr. S. Wang
dr. S. Wang
Academic year2022
Starting block
Application procedureYou apply via OSIRIS Student
Registration using OSIRISYes
After completing the course, the student is able to:
  • Perform a practical and/or theoretical research project on a specific part/problem in the field of Information Retrieval.
  • Present, discuss and defend the ideas, progress and problems of the research project to an audience of peers.
  • Present the result of the research in the form of a short research paper.
Information Retrieval (IR) is the discipline that studies the techniques and tools to search for relevant information in a large amount of data. The extensive use of IR systems for searching information in text, images and other multimedia data is one of the most remarkable success stories of Computer Science and Human-Computer Interaction.
This course is a natural follow-up to the course Foundations of Information Retrieval (201600076). In this course, students participate actively in the ongoing research at the University of Twente. The students work in small groups of 2-3 students on a practical and/or theoretical problem in the field of Information Retrieval. The students need to design, implement and evaluate a technical solution to the problem. Solutions can be tested using data from international evaluation activities such as the Text REtrieval Conference (TREC) and the Cross-Language Evaluation Forum (CLEF) or validated using domain-specific metrics.
There will be three meetings during the course, one introductory meeting to explain the possible assignments and the organization of the course, and the other two will be used for the groups to present their intermediate progress or final results to the fellow students.
The course will be graded based on the quality of the work (solution design, implementation, evaluation and presentation) as determined through progress presentations, final demonstration and the report of the project. The data and the implementation will be published as open data and open source software.
Assumed previous knowledge
Preferably Foundations of Information Retrieval or any of the following courses: Machine Learning I, Data Science or Natural Language Processing.
Participating study
Master Computer Science
Participating study
Master Interaction Technology
Required materials
Recommended materials
Instructional modes
Presence dutyYes

Project supervised
Presence dutyYes

Final report

Kies de Nederlandse taal