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RUSSE: The First Workshop on Russian Semantic Similarity

Panchenko, Alexander ; Loukachevitch, Natalia V. ; Ustalov, Dmitry ; Paperno, Denis ; Meyer, Christian M. ; Konstantinova, Natalia (2015)
RUSSE: The First Workshop on Russian Semantic Similarity.
Moscow, Russia
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (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.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2015
Autor(en): Panchenko, Alexander ; Loukachevitch, Natalia V. ; Ustalov, Dmitry ; Paperno, Denis ; Meyer, Christian M. ; Konstantinova, Natalia
Art des Eintrags: Bibliographie
Titel: RUSSE: The First Workshop on Russian Semantic Similarity
Sprache: Englisch
Publikationsjahr: Mai 2015
Buchtitel: Proceedings of the International Conference on Computational Linguistics and Intellectual Technologies (Dialogue)
Veranstaltungsort: Moscow, Russia
URL / URN: http://www.dialog-21.ru/digests/dialog2015/materials/pdf/Pan...
Kurzbeschreibung (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.

Freie Schlagworte: UKP_a_ENLP;UKP_reviewed
ID-Nummer: TUD-CS-2015-0104
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Ubiquitäre Wissensverarbeitung
DFG-Graduiertenkollegs
DFG-Graduiertenkollegs > Graduiertenkolleg 1994 Adaptive Informationsaufbereitung aus heterogenen Quellen
Hinterlegungsdatum: 31 Dez 2016 14:29
Letzte Änderung: 17 Sep 2018 16:03
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