Multi-task learning for cross-lingual sentiment analysis (CROSBI ID 701824)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Thakkar, Gaurish ; Mikelić Preradović, Nives ; Tadić, Marko
engleski
Multi-task learning for cross-lingual sentiment analysis
This paper presents a cross-lingual sentiment analysis of news articles using zero-shot and few-shot learning. The study aims to classify the Croatian news articles with the positive, negative, and neu- tral sentiment using the Slovene dataset. The system is based on a trilin- gual BERT-based model trained in three languages: English, Slovene, Croatian. The paper analyses different setups of using datasets in two languages and proposes a simple multi-task model to perform sentiment classification. The evaluation is performed using the few-shot and zero- shot scenarios in single-task and multi-task experiments for Croatian and Slovene.
sentiment analysis ; cross-lingual ; transfer learning ; multi-task learning ; news sentiment ; under-resourced languages
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
Podaci o prilogu
76-84.
2021.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 2nd International Workshop on Cross-lingual Event-centric Open Analytics
Demidova, Elena ; Hakimov, Sherzod ; Winters, Jane ; Tadić, Marko
Ljubljana:
1613-0073
Podaci o skupu
2nd International Workshop on Cross-lingual Event-centric Open Analytics (CLEOPATRA 2021)
predavanje
12.04.2021-12.04.2021
Ljubljana, Slovenija