Quality of Word Vectors and Its Impact on Named Entity Recognition in Czech

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F20%3A43918937" target="_blank" >RIV/62156489:43110/20:43918937 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.11118/ejobsat.2020.010" target="_blank" >https://doi.org/10.11118/ejobsat.2020.010</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.11118/ejobsat.2020.010" target="_blank" >10.11118/ejobsat.2020.010</a>

Result language

angličtina

Original language name

Quality of Word Vectors and Its Impact on Named Entity Recognition in Czech

Original language description

Named Entity Recognition (NER) focuses on finding named entities in text and classifying them into one of the entity types. Modern state-of-the-art NER approaches avoid using hand-crafted features and rely on feature-inferring neural network systems based on word embeddings. The paper analyzes the impact of different aspects related to word embeddings on the process and results of the named entity recognition task in Czech, which has not been investigated so far. Various aspects of word vectors preparation were experimentally examined to draw useful conclusions. The suitable settings in different steps were determined, including the used corpus, number of word vectors dimensions, used text preprocessing techniques, context window size, number of training epochs, and word vectors inferring algorithms and their specific parameters. The paper demonstrates that focusing on the process of word vectors preparation can bring a significant improvement for NER in Czech even without using additional language independent and dependent resources.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

European Journal of Business Science and Technology

ISSN

2336-6494

e-ISSN

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Volume of the periodical

6

Issue of the periodical within the volume

2

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

16

Pages from-to

154-169

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85099840520