Bachelor
2023/2024![Expected Learning Outcomes](/f/src/global/i/edu/results.svg)
![Interim Assessment](/f/src/global/i/edu/intermediate_certification.svg)
![Bibliography](/f/src/global/i/edu/library.svg)
Introduction to Formal Concept Analysis
Type:
Elective course (Fundamental and Computational Linguistics)
Area of studies:
Fundamental and Applied Linguistics
Delivered by:
School of Linguistics
Where:
Faculty of Humanities
When:
4 year, 3 module
Mode of studies:
distance learning
Online hours:
20
Open to:
students of all HSE University campuses
Instructors:
Ilya Makarchuk
Language:
English
ECTS credits:
3
Contact hours:
6
Course Syllabus
Abstract
This online course is an introduction into formal concept analysis (FCA). It will provide you with tools for understanding the data by representing it as a hierarchy of concepts or, more exactly, a concept lattice. You will learn some of data analysis and knowledge acquisition techniques, as well as the theoretical foundations of formal concept analysis. The course also covers FCA-based approaches to clustering and dependency mining.
Prerequisites are basic knowledge of elementary set theory, propositional logic, and probability theory.
Expected Learning Outcomes
- По окончании курса студенты смогут использовать математические методы и вычислительные средства анализа формальных понятий в собственных исследовательских проектах, связанных с обработкой данных. Среди прочего, студенты узнают о подходах на основе AФП к кластеризации и анализу зависимостей.
Interim Assessment
- 2023/2024 3rd moduleПо правилам курса https://edu.hse.ru/enrol/index.php?id=136226
Bibliography
Recommended Core Bibliography
- Ivic, A., Krätzel, E., Kühleitner, M., & Nowak, W. G. (2004). Lattice points in large regions and related arithmetic functions: Recent developments in a very classic topic. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsarx&AN=edsarx.math%2f0410522
Recommended Additional Bibliography
- Dalla Vecchia, R. (2015). The Relationship between Big Data and Mathematical Modeling: A Discussion in a Mathematical Education Scenario. Themes in Science and Technology Education, 8(2), 95–103. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1131006