D 2016

RuSkELL: Online Language Learning Tool for Russian Language

APRESJAN, Valentina, Vít BAISA, Olga BUIVOLOVA and Olga KULTEPINA

Basic information

Original name

RuSkELL: Online Language Learning Tool for Russian Language

Authors

APRESJAN, Valentina (643 Russian Federation), Vít BAISA (203 Czech Republic, guarantor, belonging to the institution), Olga BUIVOLOVA (643 Russian Federation) and Olga KULTEPINA (643 Russian Federation)

Edition

Tbilisi, Proceedings of the XVII EURALEX International congress, p. 292-299, 8 pp. 2016

Publisher

Ivane Javakhishvili Tbilisi State University

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Georgia

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

RIV identification code

RIV/00216224:14330/16:00090690

Organization unit

Faculty of Informatics

ISBN

978-9941-13-542-2

UT WoS

000392695200030

Keywords in English

online language tool; Sketch Engine for Language Learning; sketches; collocations

Tags

International impact, Reviewed
Změněno: 20/7/2018 14:36, Mgr. Michal Petr

Abstract

V originále

RuSkELL ("Russian + Sketch Engine for Language Learning") is a new online resource intended for researchers and learners of Russian. It incorporates a specially pre-processed corpus and the interface which allows users to search for phrases in sentences, extract salient collocates and show similar words. The tool builds upon its English counterpart SkELL (Baisa & Suchomel 2014). The aim of the project is to adapt the existing SkELL tool to Russian, improve its performance and make it user-friendly to Russian users. The existing problems include errors in query output and insufficiently transparent interface. The project aspires to solve them by 1) modifying Sketch grammar rules to exclude irrelevant output and to add informative collocations unaccounted for in the existing Sketch grammar; 2) providing collocation groups with easy-to-understand labels in Russian. We describe the process of building the language data and problems we need to address to accommodate the tool for the specificities of the Russian language.

Links

LM2015071, research and development project
Name: Jazyková výzkumná infrastruktura v České republice (Acronym: LINDAT-Clarin)
Investor: Ministry of Education, Youth and Sports of the CR
MUNI/A/0945/2015, interní kód MU
Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace V.
Investor: Masaryk University, Category A
7F14047, research and development project
Name: Harvesting big text data for under-resourced languages (Acronym: HaBiT)
Investor: Ministry of Education, Youth and Sports of the CR