Human and Machine Judgements for Russian Semantic Relatedness / Panchenko Alexander,Ustalov Dmitry,Arefyev Nikolay,Paperno Denis,Konstantinova Natalia,Loukachevitch Natalia,Biemann Chris // . - 2017. - V. 661, l. . - P. 221-235.

ISSN/EISSN:

1865-0929 / нет данных

Type:

Proceedings Paper

Abstract:

Semantic relatedness of terms represents similarity of meaning by a numerical score. On the one hand, humans easily make judgements about semantic relatedness. On the other hand, this kind of information is useful in language processing systems. While semantic relatedness has been extensively studied for English using numerous language resources, such as associative norms, human judgements and datasets generated from lexical databases, no evaluation resources of this kind have been available for Russian to date. Our contribution addresses this problem. We present five language resources of different scale and purpose for Russian semantic relatedness, each being a list of triples (wordi, wordj, similarityij). Four of them are designed for evaluation of systems for computing semantic relatedness, complementing each other in terms of the semantic relation type they represent. These benchmarks were used to organise a shared task on Russian semantic relatedness, which attracted 19 teams. We use one of the best approaches identified in this competition to generate the fifth high-coverage resource, the first open distributional thesaurus of Russian. Multiple evaluations of this thesaurus, including a large-scale crowdsourcing study involving native speakers, indicate its high accuracy.

Author keywords:

Semantic similarity; Semantic relatedness; Evaluation; Distributional thesaurus; Crowdsourcing; Language resources SIMILARITY; WORDNET

DOI:

10.1007/978-3-319-52920-2\_21

Web of Science ID:

ISI:000407059600021

Соавторы в МНС:

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Другие поля

Поле	Значение
Editor	Ignatov, DI and Khachay, MY and Labunets, VG and Loukachevitch, N and Nikolenko, SI and Panchenko, A and Savchenko, AV and Vorontsov, K
Booktitle	ANALYSIS OF IMAGES, SOCIAL NETWORKS AND TEXTS, AIST 2016
Series	Communications in Computer and Information Science
Note	5th International Conference on Analysis of Images, Social Networks, and Texts (AIST), Yekaterinburg, RUSSIA, APR 07-09, 2016
Organization	Exactpro; OK Ru; Ctr Informat Technologies
Publisher	SPRINGER INTERNATIONAL PUBLISHING AG
Address	GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
Language	English
ISBN	978-3-319-52920-2; 978-3-319-52919-6
Keywords-Plus	SIMILARITY; WORDNET
Author-Email	panchenko@lt.informatik.tu-darmstadt.de dmitry.ustalov@urfu.ru louk\_nat@mail.ru denis.paperno@unitn.it n.konstantinova@wlv.ac.uk biem@lt.informatik.tu-darmstadt.de
Funding-Acknowledgement	Russian Foundation for Basic Research (RFBR) {[}16-37-00354]; European Research Council (ERC) {[}283554]; Russian Foundation for Humanities (RFH) {[}15-04-12017]; Deutsche Forschungsgemeinschaft (DFG)
Funding-Text	We would like to acknowledge several funding organisations that partially supported this research. Dmitry Ustalov was supported by the Russian Foundation for Basic Research (RFBR) according to the research project no. 16-37-00354. Denis Paperno was supported by the European Research Council (ERC) 2011 Starting Independent Research Grant no. 283554 (COMPOSES). Natalia Loukachevitch was supported by Russian Foundation for Humanities (RFH), grant no. 15-04-12017. Alexander Panchenko was supported by the Deutsche Forschungsgemeinschaft (DFG) under the project ``Joining Ontologies and Semantics Induced from Text (JOIN-T){''}.
Number-of-Cited-References	43
Doc-Delivery-Number	BI1XP