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.
Muhammad Shahid Iqbal Malik presented the report at Lab's seminar
MMCP postdoc Muhammad Shahid Iqbal Malik presented his report at the traditional laboratory seminar.
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.
Nikolay Arefyev and Maxim Rachinskiy took the 1st place at LSCDiscover
The laboratory members took 1st place in the LSCDiscovery.
Dmitry Ignatov had a talk on FCS's Colloquium meeting
MMCP Lab Head presented the report at FCS colloquium.
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.