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Towards Useful Word Embeddings: Evaluation on Information Retrieval, Text Classification, and Language Modeling

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F20%3A00117105" target="_blank" >RIV/00216224:14330/20:00117105 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.fi.muni.cz/usr/sojka/papers/raslan-2020-novotny-stefanik-luptak-sojka.pdf" target="_blank" >https://www.fi.muni.cz/usr/sojka/papers/raslan-2020-novotny-stefanik-luptak-sojka.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Towards Useful Word Embeddings: Evaluation on Information Retrieval, Text Classification, and Language Modeling

  • Original language description

    <p>Since the seminal work of Mikolov et al. (2013), word vectors of log-bilinear models have found their way into many NLP applications and were extended with the positional model.</p> <p>Although the positional model improves accuracy on the intrinsic English word analogy task, prior work has neglected its evaluation on extrinsic end tasks, which correspond to real-world NLP applications.</p> <p>In this paper, we describe our first steps in evaluating positional weighting on the information retrieval, text classification, and language modeling extrinsic end tasks.</p>

  • 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

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2020

  • 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 Fourteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2020

  • ISBN

    9788026316008

  • ISSN

    2336-4289

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    37-46

  • Publisher name

    Tribun EU

  • Place of publication

    Brno

  • Event location

    online

  • Event date

    Dec 8, 2020

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article

    000655471300004