RusNLP: Innopolis University

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
Deep Embeddings For Brand Detection In Product Titles	Kholodov Y. Kulagin A. Gavrilin Y.	Innopolis University	AIST	2019	Show tasks (experimental!) Морфологический анализ Дистрибутивная семантика Построение конкордансов
Rurebus-2020 Shared Task: Russian Relation Extraction For Business	Tutubalina E. V. Artemova E. L. Ivanov V. V. Batura T. V. Ivanin V. A. Sarkisyan V. V. Smurov I. M.	Kazan (Volga Region) Federal University, Kazan, Russia National Research University Higher School of Economics Moscow Institute of Physics and Technology, Moscow, Russia Innopolis University ABBYY, Moscow, Russia Novosibirsk State University, Novosibirsk, Russia Lomonosov Moscow State University, Moscow, Russia	Dialogue	2020	Show tasks (experimental!) Построение конкордансов Морфологический анализ Автоматическое реферирование
Efficiency Of Text Readability Features In Russian Academic Texts	Solovev V. D. Ivanov V. V. Solnyshkina M. I.	Kazan (Volga Region) Federal University, Kazan, Russia Innopolis University	Dialogue	2018	Show tasks (experimental!) Морфологический анализ Построение конкордансов Автоматическое реферирование