Bachelor 2023/2024

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.

Learning Objectives

• Способность использовать математические модели для понимания данных

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.

Course Contents

• Онлайн-курс

Assessment Elements

• Тесты
• Итоговый тест

Interim Assessment

• 2023/2024 3rd module
  По 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

Authors

• LANDER Iurii ALEKSANDROVICH