A survey on semantic representations for text summarization (2021)
- Authors:
- USP affiliated authors: PARDO, THIAGO ALEXANDRE SALGUEIRO - ICMC ; INÁCIO, MARCIO LIMA - ICMC
- Unidade: ICMC
- Subjects: PROCESSAMENTO DE LINGUAGEM NATURAL; SEMÂNTICA; RESUMOS
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: ICMC-USP
- Publisher place: São Carlos
- Date published: 2021
- Source:
- ISSN: 0103-2569
-
ABNT
INÁCIO, Marcio Lima e PARDO, Thiago Alexandre Salgueiro. A survey on semantic representations for text summarization. . São Carlos: ICMC-USP. Disponível em: https://repositorio.usp.br/directbitstream/cc6947f2-35d6-440f-8dea-1c8caf4e8671/3056813.pdf. Acesso em: 03 jun. 2024. , 2021 -
APA
Inácio, M. L., & Pardo, T. A. S. (2021). A survey on semantic representations for text summarization. São Carlos: ICMC-USP. Recuperado de https://repositorio.usp.br/directbitstream/cc6947f2-35d6-440f-8dea-1c8caf4e8671/3056813.pdf -
NLM
Inácio ML, Pardo TAS. A survey on semantic representations for text summarization [Internet]. 2021 ;[citado 2024 jun. 03 ] Available from: https://repositorio.usp.br/directbitstream/cc6947f2-35d6-440f-8dea-1c8caf4e8671/3056813.pdf -
Vancouver
Inácio ML, Pardo TAS. A survey on semantic representations for text summarization [Internet]. 2021 ;[citado 2024 jun. 03 ] Available from: https://repositorio.usp.br/directbitstream/cc6947f2-35d6-440f-8dea-1c8caf4e8671/3056813.pdf - Semantic-based opinion summarization
- The AMR-PT corpus and the semantic annotation of challenging sentences from journalistic and opinion texts
- Word embeddings at post-editing
- Sumarização de Opinião com base em Abstract Meaning Representation
- NMT and PBSMT error analyses in english to brazilian portuguese automatic translations
- Natural language generation: recently learned lessons, directions for semantic representation-based approaches, and the case of brazilian portuguese language
- Formalizing CST-based content selection operations
- DiZer 2.0: a web interface for discourse parsing
- Semi-supervised never-ending learning in rhetorical relation identification
- Improving content selection for update summarization with subtopic-enriched sentence ranking functions
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