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Regular version of the site

Introduction to Formal Concept Analysis

2024/2025
Academic Year
ENG
Instruction in English
3
ECTS credits
Course type:
Elective course
When:
4 year, 3 module

Instructor


Bazhukov, Maxim

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

Learning Objectives

  • Способность использовать математические модели для понимания данных
Expected Learning Outcomes

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

Course Contents

  • Онлайн-курс
Assessment Elements

Assessment Elements

  • non-blocking Тесты
  • non-blocking Итоговый тест
Interim Assessment

Interim Assessment

  • 2024/2025 3rd module
    По правилам курса https://edu.hse.ru/enrol/index.php?id=136226
Bibliography

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