Computing with words
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Teaching
Details
Faculty Faculty of Science and Medicine Domain Computer Science Code UE-SIN.07623 Languages English Type of lesson Lecture
Level Master Semester AS-2026 Schedules and rooms
Summary schedule Monday 14:15 - 17:00, Hebdomadaire (Autumn semester)
Teaching
Responsibles - Portmann Edy
Teachers - Portmann Edy
Description Computing with words is a mathematical model that processes linguistic information, as words and phrases, instead of numbers for computation and reasoning, thus making computing more human-oriented. It is based on fuzzy logic and allows computers to process vague, imprecise information to solve problems that are difficult to quantify.
Following demo-driven research, the idea of this design studio is to introduce students into computing with words. Over the course of the semester, the demo-driven research methods let the students to develop and test prototypes. Using fuzzy logic, its process enables (a pair of) students to convert natural language into a fuzzy representation, to perform computations on that representation and then, to convert the result back into a human-understandable words and phrases.
At the kick-off meeting, a prototyping case will be introduced, which the teams will work on. The prototypes will be implemented by the group using an extended Raspberry Pi and EmotiBit set (50% of the grade). The remaining 50% of the grade will be divided between exercises, tutorials, and journals (25%) as well as an oral exam (25%). Note that a maximum of 10 students can register. Email the course instructors for registration; first come, first served.
Training objectives On successful completion of this design studio class*, the students will have:
- Learned about fuzzy logic-based computing with words and perceptions, as a kind of embodied intelligence,
- Became familiar with demo-driven research (within a group of two) by designing, engineering, and evaluating a focusing guide,
- Developed an understanding of somatic memory, by implementing interactive Raspberry Pi prototypes.*Note that for certain projects, the students must have attended an introduction to the FabLab before using its machines.
Comments MSc-CS BENEFRI - (Code Ue: 53131 / Track: T5, Code Ue: 63131 / Track 6) The exact date and time of this course as well as the complete course list can be found at https://mcs.unibnf.ch/.
Course and exam registration on ACADEMIA (not myunifr.ch). Please follow the instructions on https://mcs.unibnf.ch/organization/
Softskills No Off field No BeNeFri Yes Mobility Yes UniPop No Documents
Bibliography H.H. Bothe, E. Portmann (2026). Computing with Words: An Introduction to Fuzzy Logic Use-Cases with Theory and Applications. Springer.
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Dates and rooms
Date Hour Type of lesson Place 14.09.2026 14:15 - 17:00 Cours 21.09.2026 14:15 - 17:00 Cours 28.09.2026 14:15 - 17:00 Cours 05.10.2026 14:15 - 17:00 Cours 12.10.2026 14:15 - 17:00 Cours 19.10.2026 14:15 - 17:00 Cours 26.10.2026 14:15 - 17:00 Cours 02.11.2026 14:15 - 17:00 Cours 09.11.2026 14:15 - 17:00 Cours 23.11.2026 14:15 - 17:00 Cours 30.11.2026 14:15 - 17:00 Cours 07.12.2026 14:15 - 17:00 Cours 14.12.2026 14:15 - 17:00 Cours -
Assessments methods
Exam
Assessments methods By rating -
Assignment
Valid for the following curricula: Ma - Business Communication : Business Informatics - 90 ECTS
Version: 2024-SA_V03
Business Informatics > Business Informatics Courses > Module Informatik > Data ScienceBusiness Informatics > Business Informatics Courses > Module Wirtschaftsinformatik > TMD: Technologies and Modelling for Digitalization
Ma - Business Informatics - 90 ECTS
Version: 2020-SA_V01
Classes - min. 45 ECTS > Module IT and IT Management - min 8 ECTS > Data ScienceClasses - min. 45 ECTS > Module IT and IT Management - min 8 ECTS > TMD: Technologies and Modelling for DigitalizationClasses - min. 45 ECTS > Modules IT Management - min. 22 ECTS > TMD: Technologies and Modelling for Digitalization
MiMa - Business Informatics - 30 ECTS
Version: 2020-SA_V01
Courses > Modules in Computer Science > Data ScienceCourses > Modules in Business Informatics > TMD: Technologies and Modelling for Digitalization
MiMa - Data Analytics - 30 ECTS
Version: 2020-SA_V01
Maximum of 9 ECTS credits can be chosen from courses in module T6 (Data Science) of the MSc in Computer Science and/or modules DADS and TMD of the MSc in Business Informatics. > Data ScienceMaximum of 9 ECTS credits can be chosen from courses in module T6 (Data Science) of the MSc in Computer Science and/or modules DADS and TMD of the MSc in Business Informatics. > TMD: Technologies and Modelling for Digitalization
