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Mnogoznal : an unsupervised system for word sense disambiguation
Ustalov, Dmitry
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Teslenko, Denis
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Panchenko, Alexander
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Chernoskutov, Mikhail
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DOI:
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https://doi.org/10.1109/SIBIRCON.2017.8109857
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URL:
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https://www.researchgate.net/publication/321122015...
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Additional URL:
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http://ieeexplore.ieee.org/document/8109857/
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Document Type:
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Conference or workshop publication
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Year of publication:
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2017
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Book title:
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2017 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON)
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Page range:
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147-150
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Conference title:
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2017 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON)
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Location of the conference venue:
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Novosibirsk, Russia
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Date of the conference:
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September 18-22, 2017
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Publisher:
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Rodionov, Alexey
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Place of publication:
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Piscataway, NJ
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Publishing house:
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IEEE
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ISBN:
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978-1-5386-1597-3 , 978-1-5386-1596-6 , 978-1-5386-1595-9
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Publication language:
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English
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Institution:
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School of Business Informatics and Mathematics > Information Systems III: Enterprise Data Analysis (Ponzetto 2016-)
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Subject:
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004 Computer science, internet
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Abstract:
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In this paper, we present Mnogoznal, an unsupervised system for word sense disambiguation. Given a sentence, the system chooses the most relevant sense of each input word w.r.t. to the semantic similarity between the given sentence and the synset constituting the sense of the target word. Mnogoznal has two modes of operation. The sparse mode uses the traditional vector space model to estimate the most similar word sense corresponding to its context. The dense mode, instead, uses synset embeddings to cope with the sparsity problem. We describe the architecture of the present system and also conduct its preliminary evaluation on three different lexical semantic resources for Russian. We found that the dense mode substantially outperform the sparse one on all the datasets as according to the adjusted Rand index computed on a gold standard dataset.
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
 Search Authors in
BASE:
Ustalov, Dmitry
;
Teslenko, Denis
;
Panchenko, Alexander
;
Chernoskutov, Mikhail
Google Scholar:
Ustalov, Dmitry
;
Teslenko, Denis
;
Panchenko, Alexander
;
Chernoskutov, Mikhail
ORCID:
Ustalov, Dmitry  ORCID: https://orcid.org/0000-0002-9979-2188, Teslenko, Denis, Panchenko, Alexander ORCID: https://orcid.org/0000-0001-6097-6118 and Chernoskutov, Mikhail
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