Curriculum Learning in Sentiment Analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43955686" target="_blank" >RIV/49777513:23520/19:43955686 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-26061-3_45" target="_blank" >http://dx.doi.org/10.1007/978-3-030-26061-3_45</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-26061-3_45" target="_blank" >10.1007/978-3-030-26061-3_45</a>
Alternative languages
Result language
angličtina
Original language name
Curriculum Learning in Sentiment Analysis
Original language description
This work deals with curriculum learning for deep learning models for the sentiment analysis task. We design a new way of curriculum learning for text data. We reorder the training dataset to introduce the simpler examples first. We estimate the difficulty of the examples by measuring the length of the sentences. The simple examples are supposed to be shorter. We also experiment with measuring the frequency of the words, which is a technique designed by earlier researchers. We attempt to evaluate changes in the overall accuracy of the models using both curriculum learning techniques. Our experiments do not show an increase in accuracy for any of the methods. Nevertheless, we reach a new state of the art in the sentiment analysis for Czech as a by-product of our effort
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
<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Speech and Computer
ISBN
978-3-030-26060-6
ISSN
0302-9743
e-ISSN
—
Number of pages
7
Pages from-to
444-450
Publisher name
Springer
Place of publication
Cham
Event location
Istanbul
Event date
Aug 20, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—