Cross-document anaphora extraction from Russian user-generated content in the medical field

Student: Kutsev Dmitry

Supervisor: Irina Efimenko

Educational Programme: Computational Linguistics (Master)

Year of Graduation: 2021

The paper focuses on the cross-textual anaphora resolution from medicine-related content generated by Russian users. The initial research involved an analysis of anaphora resolution methods and their application. The data collected and annotated for the experiment can be used in further studies of anaphora resolution. Three algorithms were developed for anaphora resolution in the Russian language: one is a rule-based algorithm, the other two follow machine-learning approach. The solutions obtained in the course of research can be used in the systems of information processing and information extraction from medical data sources. The code and data set used for developing the modules are avaliable in GitHub repository.

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