Computing with words

  • 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.

  • 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 Science
    Business 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 Science
    Classes - min. 45 ECTS > Module IT and IT Management - min 8 ECTS > TMD: Technologies and Modelling for Digitalization
    Classes - 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 Science
    Courses > 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 Science
    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. > TMD: Technologies and Modelling for Digitalization