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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

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • 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