Latent Dirichlet Allocation (LDA) Approximation Analysis of Financial-Related Text Messages
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F23%3APU147991" target="_blank" >RIV/00216305:26510/23:PU147991 - isvavai.cz</a>
Result on the web
<a href="https://ecocyb.ase.ro/nr2023_1/2023_1_17_ZuzanaJANKOVA_online.pdf" target="_blank" >https://ecocyb.ase.ro/nr2023_1/2023_1_17_ZuzanaJANKOVA_online.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.24818/18423264/57.1.23.17" target="_blank" >10.24818/18423264/57.1.23.17</a>
Alternative languages
Result language
angličtina
Original language name
Latent Dirichlet Allocation (LDA) Approximation Analysis of Financial-Related Text Messages
Original language description
Topic modeling is one of the most widely used NLP techniques for discovering hidden patterns and latent relationships in text documents. Latent Dirichlet Allocation (LDA) is one of the most popular methods in this field. There are different approaches to tuning the parameters of LDA models such as Gibbs sampling, variational method, or expected propagation. This paper aims to compare individual LDA parameter tuning approaches with respect to their performance and accuracy on textual data from the financial domain. From our results, it can be concluded that for text datasets obtained from financial social platforms, stochastic solvers are the most suitable and especially less time consuming than approximation methods.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50206 - Finance
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Economic Computation and Economic Cybernetics Studies and Research
ISSN
0424-267X
e-ISSN
1842-3264
Volume of the periodical
57
Issue of the periodical within the volume
1
Country of publishing house
RO - ROMANIA
Number of pages
16
Pages from-to
267-282
UT code for WoS article
000960039800017
EID of the result in the Scopus database
2-s2.0-85151554545