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RUSSE: The First Workshop on Russian Semantic Similarity

Panchenko, Alexander and Loukachevitch, Natalia V. and Ustalov, Dmitry and Paperno, Denis and Meyer, Christian M. and Konstantinova, Natalia (2015):
RUSSE: The First Workshop on Russian Semantic Similarity.
In: Proceedings of the International Conference on Computational Linguistics and Intellectual Technologies (Dialogue), Moscow, Russia, [Online-Edition: http://www.dialog-21.ru/digests/dialog2015/materials/pdf/Pan...],
[Conference or Workshop Item]

Abstract

The paper gives an overview of the Russian Semantic Similarity Evaluation (RUSSE) shared task held in conjunction with the Dialogue 2015 conference. There exist a lot of comparative studies on semantic similarity, yet no analysis of such measures was ever performed for the Russian language. Exploring this problem for the Russian language is even more interesting, because this language has features, such as rich morphology and free word order, which make it significantly different from English, German, and other well-studied languages. We attempt to bridge this gap by proposing a shared task on the semantic similarity of Russian nouns. Our key contribution is an evaluation methodology based on four novel benchmark datasets for the Russian language. Our analysis of the 105 submissions from 19 teams reveals that successful approaches for English, such as distributional and skip-gram models, are directly applicable to Russian as well. On the one hand, the best results in the contest were obtained by sophisticated supervised models that combine evidence from different sources. On the other hand, completely unsupervised approaches, such as a skip-gram model estimated on a large-scale corpus, were able score among the top 5 systems.

Item Type: Conference or Workshop Item
Erschienen: 2015
Creators: Panchenko, Alexander and Loukachevitch, Natalia V. and Ustalov, Dmitry and Paperno, Denis and Meyer, Christian M. and Konstantinova, Natalia
Title: RUSSE: The First Workshop on Russian Semantic Similarity
Language: English
Abstract:

The paper gives an overview of the Russian Semantic Similarity Evaluation (RUSSE) shared task held in conjunction with the Dialogue 2015 conference. There exist a lot of comparative studies on semantic similarity, yet no analysis of such measures was ever performed for the Russian language. Exploring this problem for the Russian language is even more interesting, because this language has features, such as rich morphology and free word order, which make it significantly different from English, German, and other well-studied languages. We attempt to bridge this gap by proposing a shared task on the semantic similarity of Russian nouns. Our key contribution is an evaluation methodology based on four novel benchmark datasets for the Russian language. Our analysis of the 105 submissions from 19 teams reveals that successful approaches for English, such as distributional and skip-gram models, are directly applicable to Russian as well. On the one hand, the best results in the contest were obtained by sophisticated supervised models that combine evidence from different sources. On the other hand, completely unsupervised approaches, such as a skip-gram model estimated on a large-scale corpus, were able score among the top 5 systems.

Title of Book: Proceedings of the International Conference on Computational Linguistics and Intellectual Technologies (Dialogue)
Uncontrolled Keywords: UKP_a_ENLP;UKP_reviewed
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Ubiquitous Knowledge Processing
DFG-Graduiertenkollegs
DFG-Graduiertenkollegs > Research Training Group 1994 Adaptive Preparation of Information from Heterogeneous Sources
Event Location: Moscow, Russia
Date Deposited: 31 Dec 2016 14:29
Official URL: http://www.dialog-21.ru/digests/dialog2015/materials/pdf/Pan...
Identification Number: TUD-CS-2015-0104
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