RusNLP: Rybka R. B.

Space-separated query words: ?One main thing: this is not a full-text word search. It is based on the principle of distributional semantics: having a query vector compiled from the query words, we use cosine distance to find the nearest texts in a bilingual vector space — this is how we search for papers that are close seamantically, regardless of the language and the presence of specific words. If you want to find papers that contain specific words in the title, use the metadata search below.

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Paper title	Paper author	Affiliation	Conference	Year	Tasks
Named Entity Recognition In Russian With Word Representation Learned By A Bidirectional Language Model	Filchenkov Andrey Konoplich G. Putin E. Rybka R. B.	National Research Centre “Kurchatov Institute”, Moscow, Russia ITMO University, Saint-Petersburg, Russia	AINL	2018	Show tasks (experimental!) Дистрибутивная семантика Морфологический анализ Построение конкордансов
Research Of A Deep Learning Neural Network Effectiveness For A Morphological Parser Of Russian Language	Moloshnikov I. A. Voronina I. Gudovskikh D. V. Rybka R. B. Ivanov I. Sboev A. G.	National Research Centre “Kurchatov Institute”, Moscow, Russia National Research Nuclear University «MEPhI», Moscow, Russia Moscow Technological University (MIREA) Voronezh State University, Russian Federation	Dialogue	2017	Show tasks (experimental!) Морфологический анализ Дистрибутивная семантика Построение конкордансов