Learning Inter-Lingual Document Representations via Concept Compression

Marc Lenz*, Tsegaye Misikir Tashu, Tomáš Horváth

*Corresponding author voor dit werk

    OnderzoeksoutputAcademicpeer review

    1 Citaat (Scopus)

    Samenvatting

    In this work, we proposed a novel approach to derive inter-lingual document representations. The introduced methods aim to enhance the quality of content-based Multilingual Document Recommendation and information retrieval Systems. The main idea centers around creating inter-lingual representations by using mappings to align monolingual representation spaces. According to the experimental results carried out on JRC-Acquis and EU bookshop multilingual corpora, the proposed concept compression approach has outperformed the traditional cross-lingual retrieval and recommendations methods.

    Originele taal-2English
    TitelIntelligent Data Engineering and Automated Learning - 22nd International Conference, IDEAL 2021, Proceedings
    RedacteurenDavid Camacho, Peter Tino, Richard Allmendinger, Hujun Yin, Antonio J. Tallón-Ballesteros, Ke Tang, Sung-Bae Cho, Paulo Novais, Susana Nascimento
    Plaats van productieCham
    UitgeverijSpringer Science and Business Media Deutschland GmbH
    Pagina's268-276
    Aantal pagina's9
    ISBN van elektronische versie978-3-030-91608-4
    ISBN van geprinte versie9783030916077
    DOI's
    StatusPublished - 23-nov.-2021
    Evenement22nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2021 - Virtual, Online
    Duur: 25-nov.-202127-nov.-2021

    Publicatie series

    NaamLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume13113 LNCS
    ISSN van geprinte versie0302-9743
    ISSN van elektronische versie1611-3349

    Conference

    Conference22nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2021
    StadVirtual, Online
    Periode25/11/202127/11/2021

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