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Textual embeddings with word-type-weighted word2vec

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F24%3A00603024" target="_blank" >RIV/67985807:_____/24:00603024 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21240/24:00377340

  • Result on the web

    <a href="https://ceur-ws.org/Vol-3792/paper4.pdf" target="_blank" >https://ceur-ws.org/Vol-3792/paper4.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Textual embeddings with word-type-weighted word2vec

  • Original language description

    The increasing use of artificial neural networks for knowledge processing often lacks precise knowledge representation. To address this issue, we propose using a word-type-weighted Word2Vec model to achieve more accurate representations of individual words within sentences. Our approach incorporates weighting vector embeddings of words based on parts-of-speech predictions generated by the spaCy library. Experimental results demonstrate that, compared to simple Word2Vec, our model enhances the accuracy of recognizing the semantics of a sentence, while maintaining significantly lower computational requirements than large language models and various variants of Transformer.

  • 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

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2024

  • 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 24th Conference Information Technologies – Applications and Theory (ITAT 2024)

  • ISBN

  • ISSN

    1613-0073

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    37-42

  • Publisher name

    Technical University & CreateSpace Independent Publishing

  • Place of publication

    Aachen

  • Event location

    Drienica

  • Event date

    Sep 20, 2024

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article