Contextualised word embeddings based on transfer learning to dialogue response generation: a proposal and comparisons (2021)
- Authors:
- USP affiliated authors: HRUSCHKA, EDUARDO RAUL - EP ; COSTA, ANNA HELENA REALI - EP ; SANTOS, THOMAZ CALASANS DOS - EP
- Unidade: EP
- DOI: 10.1145/3459104.3459169
- Assunto: PROCESSAMENTO DE LINGUAGEM NATURAL
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Proceedings
- Conference titles: International Symposium on Electrical, Electronics and Information Engineering - ISEEIE
- Este artigo NÃO possui versão em acesso aberto
-
Status: Nenhuma versão em acesso aberto identificada -
ABNT
SANTOS, Thomaz Calasans dos e HRUSCHKA, Eduardo Raul e REALI COSTA, Anna Helena. Contextualised word embeddings based on transfer learning to dialogue response generation: a proposal and comparisons. 2021, Anais.. New York: Escola Politécnica, Universidade de São Paulo, 2021. Disponível em: https://doi.org/10.1145/3459104.3459169. Acesso em: 13 mar. 2026. -
APA
Santos, T. C. dos, Hruschka, E. R., & Reali Costa, A. H. (2021). Contextualised word embeddings based on transfer learning to dialogue response generation: a proposal and comparisons. In Proceedings. New York: Escola Politécnica, Universidade de São Paulo. doi:10.1145/3459104.3459169 -
NLM
Santos TC dos, Hruschka ER, Reali Costa AH. Contextualised word embeddings based on transfer learning to dialogue response generation: a proposal and comparisons [Internet]. Proceedings. 2021 ;[citado 2026 mar. 13 ] Available from: https://doi.org/10.1145/3459104.3459169 -
Vancouver
Santos TC dos, Hruschka ER, Reali Costa AH. Contextualised word embeddings based on transfer learning to dialogue response generation: a proposal and comparisons [Internet]. Proceedings. 2021 ;[citado 2026 mar. 13 ] Available from: https://doi.org/10.1145/3459104.3459169 - A framework for multi-document extractive summarization of reviews with aspect-based sentiment analysis
- On the influence of imputation in classification: practical issues
- An evolutionary algorithm for clustering data streams with a variable number of clusters
- An Experimental Study on Unsupervised Clustering-Based Feature Selection Methods
- Using both latent and supervised shared topics for multitask learning
- A study of K-means-based algorithms for constrained clustering
- Biocom_Usp: tweet sentiment analysis with adaptive boosting ensemble
- A semi-supervised approach to estimate the number of clusters per class
- Classification with multi-modal classes using evolutionary algorithms and constrained clustering
- A distance-based mutation operator for learning bayesian network structures using evolutionary algorithms
Informações sobre a disponibilidade de versões do artigo em acesso aberto coletadas automaticamente via oaDOI API (Unpaywall).
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
3287295.pdf | Direct link |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
