Construction of a Russian paraphrase corpus: unsupervised paraphrase extraction

E Pronoza, E Yagunova, A Pronoza - Information Retrieval: 9th Russian …, 2016 - Springer
This paper presents a crowdsourcing project on the creation of a publicly available corpus of
sentential paraphrases for Russian. Collected from the news headlines, such corpus could …

[图书][B] Yarn: Spinning-in-progress

P Braslavski, D Ustalov, M Mukhin, Y Kiselev - 2016 - madoc.bib.uni-mannheim.de
YARN (Yet Another RussNet), a project started in 2013, aims at creating a large open
WordNet-like thesaurus for Russian by means of crowdsourcing. The first stage of the project …

Comparing two thesaurus representations for Russian

N Loukachevitch, G Lashevich… - Proceedings of the 9th …, 2018 - aclanthology.org
In the paper we presented a new Russian wordnet, RuWordNet, which was semi-
automatically obtained by transformation of the existing Russian thesaurus RuThes. At the …

The Sociopolitical Thesaurus as a resource for automatic document processing in Russian

N Loukachevitch, B Dobrov - … of Theoretical and Applied Issues in …, 2015 - jbe-platform.com
This paper presents the structure and current state of the Sociopolitical thesaurus, which
was developed for automatic document analysis and information-retrieval applications in …

Russian lexicographic landscape: a tale of 12 dictionaries

Y Kiselev, A Krizhanovsky, P Braslavski, I Menshikov… - 2015 - elar.urfu.ru
The paper reports on quantitative analysis of 12 Russian dictionaries at three levels: 1)
headwords: The size and overlap of word lists, coverage of large corpora, and presence of …

Comparison of sentence similarity measures for Russian paraphrase identification

E Pronoza, E Yagunova - 2015 Artificial Intelligence and …, 2015 - ieeexplore.ieee.org
In this paper we analyze and compare different types of sentence similarity measures
applied to the problem of sentential paraphrase identification. We work with Russian, and all …

[PDF][PDF] Алгоритмы интеллектуального поиска на основе метода категориальных векторов

ДВ Бондарчук - Екатеринбург: УрГУПС, 2016 - sp.susu.ru
Актуальность темы. В последнее десятилетие интеллектуальный ана лиз текстовых
данных получил широкое распространение в связи потребностью многих отраслей …

[PDF][PDF] Determining the most frequent senses using Russian linguistic ontology RuThes

N Loukachevitch, I Chetviorkin - Proceedings of the workshop on …, 2015 - aclanthology.org
The paper describes a supervised approach for the detection of the most frequent senses of
words on the basis of RuThes thesaurus, which is a large linguistic ontology for Russian …

Современное состояние электронных тезаурусов русского языка: качество, полнота и доступность

ЮА Киселёв, СВ Поршнев, МЮ Мухин - Программная инженерия, 2015 - elibrary.ru
В настоящей обзорно-аналитической статье рассмотрены проблемные вопросы и
характерные особенности электронных тезаурусов русского языка …

Low-level features for paraphrase identification

E Pronoza, E Yagunova - Advances in Artificial Intelligence and Soft …, 2015 - Springer
This paper deals with the task of sentential paraphrase identification. We work with Russian
but our approach can be applied to any other language with rich morphology and free word …