Ordered Sets in Data Analysis (2022)

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General information

One semester course. 6 kredits.

Lecturer: Sergey Kuznetsov (Сергей Олегович Кузнецов)

Class teacher: Fedor Strok (Федор Владимирович Строк)

GitHub repo of the course

Students book on Arxiv

Telegram channel (this one)

Telegram chat


Type Day of week Time Place
Lectures Tuesday 11:10-12:30, 13.00-14.20 S224, Pokrovsky Blvd. 11 (Покровский б-р 11)
Seminars Tuesday 11:10-12:30, 13.00-14.20 S224, Pokrovsky Blvd. 11 (Покровский б-р 11)

Grading system

Final Grade = 0.45 * first_module + 0.55 * second_module

first_module = 0.5 * avg (homeworks) + 0.5 * test (at the end of the module)

second_module = 0.3 * avg (homeworks) + 0.4 * big homework + 0.3 * test (at the end of the module)

Homeworks -- assignments given after each lecture;

Big Homework -- three options:


Choosing this option means that you make a 30-minutes oral presentation with LaTeX-based pdf slides which is a survey of 5+ recent papers (preferably published not earlier than 2018) on the topic (see the list below) preferably taken from Q1-Q2 journals (according to Web of Science or Scopus, www.scimagojr.com) and A-A* conferences (according to CORE conference ranking http://portal.core.edu.au/conf-ranks/) like IJCAI, ICDM, NeurIPS, ICML, ECML/PKDD etc. If you want to choose articles somewhere else, you need to consult with the teacher to estimate the level of the publication you have chosen.

  • Lazy FCA
  • Neural FCA


Task description Source Deadline
Solve the problems given at the end of the first lecture. The exact problems to solve are: 3-6 Lecture 1 20.09.22


Lecture Date Topics Download materials Russian Materials Read Materials Pages Reading time
Lecture 0 Prerequisites Asymptotic notations. Complexity classes. P- and NP-complete problems. NDMT. Click Missing Click 38p 20-30 min read
Lecture 1 13.09.22 Relations, binary relations, their matrices and graphs. Operations over relations, their properties, and types of relations. Click Click Click 37p 20-30 min read
Lecture 2 27.09.22 Quasi order, partial order. Topological sorting. Dushnik-Miller theorem. Applications. Click Click Click 54p 30-40 min read
Lecture 3 11.10.22 Lattices and closures. Semilattices. Distributivity and modularity. Click Missing Click 44p 30-40 min read
Lecture 4 11.10.22 Introduction to Formal Concept Analysis. Concept lattice and implications. Click Missing Click 35p 24-26 min read


Seminar Date Topics Download materials Read Materials Pages Reading time
soon soon soon soon soon soon soon


Main literature

  • Cormen, T. H., Leiserson, C. E., Rivest, R. L., Stein, C. Introduction to Algorithms (3rd edition). – MIT Press, 2009. – 1292 pp.
  • Kuznetsov, S. O. Fitting pattern structures to knowledge discovery in big data // International conference on formal concept analysis. – Springer, Berlin, Heidelberg, 2013. – PP. 254-266.

Additional literature

  • Kuznetsov, S. O. Pattern structures for analyzing complex data // International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing. – Springer, Berlin, Heidelberg, 2009. – P. 33-44.
  • Kuznetsov, S. O. Scalable knowledge discovery in complex data with pattern structures // International Conference on Pattern Recognition and Machine Intelligence. – Springer, Berlin, Heidelberg, 2013. – P. 30-39.