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Regular version of the site

Laboratory for Models and Methods of Computational Pragmatics

Publications
Article
Triclusters of Close Values for the Analysis of 3D Data

Egurnov D., Ignatov D. I.

Automation and Remote Control. 2022. Vol. 83. No. 6. P. 894-902.

Book chapter
Triclustering in Big Data Setting

Egurnov D., Точилкин Д. С., Ignatov D. I.

In bk.: Complex Data Analytics with Formal Concept Analysis. Springer, 2022. P. 239-258.

Working paper
Object-Attribute Biclustering for Elimination of Missing Genotypes in Ischemic Stroke Genome-Wide Data In press

Ignatov D. I., Khvorykh G. V., Khrunin A. V. et al.

Lecture Notes in Computer Science. LNCS. Springer, 2020

About the Laboratory

The area of expertise of Lab is unstructured data analysis. We study recommending systems and services, develop methods for multimodal clustering and classification that allow profiling user interests based on various modalities. We do not treat data mining and machine learning models as black boxes and focus on developing interpretable algorithms.
We work in natural language processing (NLP). The focus of research lies in such areas as question-answering and information extraction. The Laboratory examines learning methods, in particular, transfer learning and domain adaptation techniques in multilingual settings, and applies these methods in practice. The Laboratory advances digital Russian studies by creating new annotated data sources, that represent society changes and such complex phenomena as education and economy digitalization.


Illustration for news: Dmitry I. Ignatov presented his report at NTR company webinar

Dmitry I. Ignatov presented his report at NTR company webinar

On November 15, 2022  Dmitry Ignatov - laboratory Head at Laboratory for Models and Methods of Computational Pragmatics, associate Professor at School of Data Analysis and Artificial Intelligence took part in NTR company webinar.

In the talk, the speaker explained how Data Mining and Formal Concept Analysis can help to solve combinatorial problems from Lattice Theory and establish connections between seemingly unrelated algebraic objects. 

Illustration for news: Nikolay Arefyev and Maxim Rachinskiy took the 1st place at LSCDiscover

Nikolay Arefyev and Maxim Rachinskiy took the 1st place at LSCDiscover

Максим Рачинский и Николай Арефьев заняли 1 место в дорожке LSCDiscovery

Illustration for news: Dmitry Ignatov had a talk on FCS's Colloquium meeting

Dmitry Ignatov had a talk on FCS's Colloquium meeting

Illustration for news: Faculty's Researchers to Present at EMNLP 2021

Faculty's Researchers to Present at EMNLP 2021

The annual Conference on Empirical Methods in Natural Language Processing (EMNLP) takes place on November 7-11, 2021.

Our Lab held the RuREBus shared task

More information about the corpus, types of relations and entities can be found in the repository of competition, which we held at the Dialog 2020 conference on RuREBus data.