KFU. Card publication. Expert Assessment of Synonymic Rows in RuWordNet

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

EXPERT ASSESSMENT OF SYNONYMIC ROWS IN RUWORDNET

Form of presentation

Articles in international journals and collections

Year of publication

2020

Язык

английский

Authors, employees of KFU

Gimaletdinova Gulnara Kamilevna, author

Solovev Valeriy Dmitrievich, author

Usmanova Liliya Abrarovna, author

Bibliographic description in the original language

Soloviev, V., Gimaletdinova, G., Khalitova, L., Usmanova, L. Expert Assessment of Synonymic Rows in RuWordNet // Analysis of Images, Social Networks and Texts (AIST'2019). CCIS, vol. 1086. (2020). Pr. 174-183.

Annotation

Analysis of Images, Social Networks and Texts

Keywords

Computer lexicography Synonymy Dictionaries of synonyms RuWordNet thesaurus Hypo-hyperonymic relationships

The name of the journal

Analysis of Images, Social Networks and Texts

URL

https://link.springer.com/chapter/10.1007/978-3-030-39575-9_18

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=221817&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Gimaletdinova Gulnara Kamilevna	ru_RU
dc.contributor.author	Solovev Valeriy Dmitrievich	ru_RU
dc.contributor.author	Usmanova Liliya Abrarovna	ru_RU
dc.date.accessioned	2020-01-01T00:00:00Z	ru_RU
dc.date.available	2020-01-01T00:00:00Z	ru_RU
dc.date.issued	2020	ru_RU
dc.identifier.citation	Soloviev, V., Gimaletdinova, G., Khalitova, L., Usmanova, L. Expert Assessment of Synonymic Rows in RuWordNet // Analysis of Images, Social Networks and Texts (AIST'2019). CCIS, vol. 1086. (2020). Pр. 174-183.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=221817&p_lang=2	ru_RU
dc.description.abstract	Analysis of Images, Social Networks and Texts	ru_RU
dc.description.abstract	This article explores the principles of synsets in the RuWordNet thesaurus and synonyms in the classical dictionaries of Russian synonyms (N = 10) to identify discrepancies and improve the principles of organising synsets in RuWordNet. The relevance of the study is determined by the demand for WordNet resources in natural language processing tasks. The authors selected 102 RuWordNet thesaurus synsets, including nouns (N = 34), adjectives (N = 34) and verbs (N = 34). The meanings of the lexemes were correlated according to the data given in Russian language thesauri (N = 2). The comparative method and an independent expert assessment of RuWordNet revealed a number of discrepancies and inaccuracies in the representation of synsets concerning polysemy, hypo-hyperonymic relationships, lexical meanings of words and parts-of-speech synonymy. On the basis of this study, the authors recommend the elimination of individual shortcomings in the construction of the RuWord-Net synsets, in particular the polysemy and parts-of-speech synonymy.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject		ru_RU
dc.title	Expert Assessment of Synonymic Rows in RuWordNet	ru_RU
dc.type	Articles in international journals and collections	ru_RU