Joint Unsupervised Learning of Semantic Representation of Words and Roles in Dependency Trees
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43949734" target="_blank" >RIV/49777513:23520/17:43949734 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.26615/978-954-452-049-6_052" target="_blank" >http://dx.doi.org/10.26615/978-954-452-049-6_052</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.26615/978-954-452-049-6_052" target="_blank" >10.26615/978-954-452-049-6_052</a>
Alternative languages
Result language
angličtina
Original language name
Joint Unsupervised Learning of Semantic Representation of Words and Roles in Dependency Trees
Original language description
In this paper, we introduce WoRel, a model that jointly learns word embeddings and a semantic representation of word relations. The model learns from plain text sentences and their dependency parse trees. The word embeddings produced by WoRel outperform Skip-Gram and GloVe in word similarity and syntactical word analogy tasks and have comparable results on word relatedness and semantic word analogy tasks. We show that the semantic representation of relations enables us to express the meaning of phrases and is a promising research direction for seman- tics at the sentence level.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017
ISBN
978-954-452-048-9
ISSN
1313-8502
e-ISSN
neuvedeno
Number of pages
7
Pages from-to
394-400
Publisher name
INCOMA Ltd.
Place of publication
Shoumen, BULGARIA
Event location
Varna, Bulgaria
Event date
Sep 2, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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