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    Detecting semantic difference: a new model based on knowledge and collocational association

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    Authors
    Taslimipoor, Shiva
    Corpas Pastor, Gloria cc
    Rohanian, Omid
    Editors
    Corpas Pastor, Gloria
    Colson, Jean-Pierre
    Issue Date
    2020-05-08
    
    Metadata
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    Abstract
    Semantic discrimination among concepts is a daily exercise for humans when using natural languages. For example, given the words, airplane and car, the word flying can easily be thought and used as an attribute to differentiate them. In this study, we propose a novel automatic approach to detect whether an attribute word represents the difference between two given words. We exploit a combination of knowledge-based and co-occurrence features (collocations) to capture the semantic difference between two words in relation to an attribute. The features are scores that are defined for each pair of words and an attribute, based on association measures, n-gram counts, word similarity, and Concept-Net relations. Based on these features we designed a system that run several experiments on a SemEval-2018 dataset. The experimental results indicate that the proposed model performs better, or at least comparable with, other systems evaluated on the same data for this task.
    Citation
    Taslimipoor, S., Corpas Pastor, G. and Rohanian, O. (2020) Detecting semantic difference: a new model based on knowledge and collocational association, in Corpas Pastor, G. and Colson, J.P. (eds) Computational Phraseology. John Benjamins, pp. 312–324.
    Publisher
    John Benjamins Publishing Company
    URI
    http://hdl.handle.net/2436/623790
    DOI
    10.1075/ivitra.24.16tas
    Additional Links
    https://benjamins.com/catalog/ivitra.24.16tas
    Type
    Chapter in book
    Language
    en
    Description
    This is an accepted manuscript of an article published by John Benjamins Publishing Company in Computational Phraseology edited by G Corpas Pastor & J-P Colson on 08/05/2020, available online: https://doi.org/10.1075/ivitra.24.16tas The accepted version of the publication may differ from the final published version.
    Series/Report no.
    IVITRA Research in Linguistics and Literature, 24
    ISBN
    9789027205353
    ae974a485f413a2113503eed53cd6c53
    10.1075/ivitra.24.16tas
    Scopus Count
    Collections
    Research Institute in Information and Language Processing

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