Opinion summarization methods: comparing and extending extractive and abstractive approaches (2017)
- Authors:
- Autor USP: PARDO, THIAGO ALEXANDRE SALGUEIRO - ICMC
- Unidade: ICMC
- DOI: 10.1016/j.eswa.2017.02.006
- Subjects: INTELIGÊNCIA ARTIFICIAL; PROCESSAMENTO DE LINGUAGEM NATURAL; RESUMOS
- Keywords: Opinion Summarization; Aspect-Based Approach; Extractive and Abstractive Summarization
- Language: Inglês
- Imprenta:
- Publisher place: Kidlington
- Date published: 2017
- Source:
- Título: Expert Systems with Applications
- ISSN: 0957-4174
- Volume/Número/Paginação/Ano: v. 78, p. 124-134, July 2017
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
CONDORI, Roque Enrique López e PARDO, Thiago Alexandre Salgueiro. Opinion summarization methods: comparing and extending extractive and abstractive approaches. Expert Systems with Applications, v. 78, p. 124-134, 2017Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2017.02.006. Acesso em: 26 fev. 2026. -
APA
Condori, R. E. L., & Pardo, T. A. S. (2017). Opinion summarization methods: comparing and extending extractive and abstractive approaches. Expert Systems with Applications, 78, 124-134. doi:10.1016/j.eswa.2017.02.006 -
NLM
Condori REL, Pardo TAS. Opinion summarization methods: comparing and extending extractive and abstractive approaches [Internet]. Expert Systems with Applications. 2017 ; 78 124-134.[citado 2026 fev. 26 ] Available from: https://doi.org/10.1016/j.eswa.2017.02.006 -
Vancouver
Condori REL, Pardo TAS. Opinion summarization methods: comparing and extending extractive and abstractive approaches [Internet]. Expert Systems with Applications. 2017 ; 78 124-134.[citado 2026 fev. 26 ] Available from: https://doi.org/10.1016/j.eswa.2017.02.006 - Clustering and hierarchical organization of opinion aspects: a corpus study
- Improving content selection for update summarization with subtopic-enriched sentence ranking functions
- Update summarization for portuguese
- Rearrangement and creation of new corpora for update and compressive summarization tasks for portuguese language
- Semi-supervised never-ending learning in rhetorical relation identification
- Update summarization: building from scratch for Portuguese and comparing to English
- Hierarchical clustering of aspects for opinion mining: a corpus study
- Multi-document summarization using semantic discourse models
- Estratégias de seleção de conteúdo com base na CST (cross-document structure theory) para sumarização automática multidocumento
- Identifying multidocument relations
Informações sobre o DOI: 10.1016/j.eswa.2017.02.006 (Fonte: oaDOI API)
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