From Bag-of-Words to pre-trained neural language models: improving automatic classification of App reviews for requirements engineering (2020)
- Authors:
- USP affiliated authors: ROMERO, ROSELI APARECIDA FRANCELIN - ICMC ; MARCACINI, RICARDO MARCONDES - ICMC ; ARAUJO, ADAILTON FERREIRA DE - ICMC ; GÔLO, MARCOS PAULO SILVA - ICMC ; VIANA, BRENO MAURICIO DE FREITAS - ICMC ; SANCHES, FELIPE PADULA - ICMC
- Unidade: ICMC
- DOI: 10.5753/eniac.2020.12144
- Subjects: APRENDIZADO COMPUTACIONAL; PROCESSAMENTO DE LINGUAGEM NATURAL; RECONHECIMENTO DE TEXTO
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: SBC
- Publisher place: Porto Alegre
- Date published: 2020
- Source:
- Título: Anais
- Conference titles: Encontro Nacional de Inteligência Artificial e Computacional - ENIAC
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: bronze
-
ABNT
ARAUJO, Adailton Ferreira de et al. From Bag-of-Words to pre-trained neural language models: improving automatic classification of App reviews for requirements engineering. 2020, Anais.. Porto Alegre: SBC, 2020. Disponível em: https://doi.org/10.5753/eniac.2020.12144. Acesso em: 29 dez. 2025. -
APA
Araujo, A. F. de, Gôlo, M. P. S., Viana, B. M. de F., Sanches, F. P., Romero, R. A. F., & Marcacini, R. M. (2020). From Bag-of-Words to pre-trained neural language models: improving automatic classification of App reviews for requirements engineering. In Anais. Porto Alegre: SBC. doi:10.5753/eniac.2020.12144 -
NLM
Araujo AF de, Gôlo MPS, Viana BM de F, Sanches FP, Romero RAF, Marcacini RM. From Bag-of-Words to pre-trained neural language models: improving automatic classification of App reviews for requirements engineering [Internet]. Anais. 2020 ;[citado 2025 dez. 29 ] Available from: https://doi.org/10.5753/eniac.2020.12144 -
Vancouver
Araujo AF de, Gôlo MPS, Viana BM de F, Sanches FP, Romero RAF, Marcacini RM. From Bag-of-Words to pre-trained neural language models: improving automatic classification of App reviews for requirements engineering [Internet]. Anais. 2020 ;[citado 2025 dez. 29 ] Available from: https://doi.org/10.5753/eniac.2020.12144 - Detecting relevant app reviews for software evolution and maintenance through multimodal one-class learning
- Opinion mining for app reviews: an analysis of textual representation and predictive models
- Hierarchical cluster labeling of software requirements using contextual word embeddings
- RE-BERT: automatic extraction of software requirements from app reviews using BERT language model
- Temporal dynamics of requirements engineering from mobile app reviews
- One-class edge classification through heterogeneous hypergraph for causal discovery
- Learning to sense from events via semantic variational autoencoder
- Text representation through multimodal variational autoencoder for one-class learning
- Text representation through multimodal variational autoencoder for one-class learning
- Improving natural product knowledge extraction from academic literature with enhanced PDF text extraction and large language models
Informações sobre o DOI: 10.5753/eniac.2020.12144 (Fonte: oaDOI API)
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