Aspect-based summarization: an approach with different levels of details to explain recommendations (2022)
- Authors:
- USP affiliated authors: MANZATO, MARCELO GARCIA - ICMC ; SOUZA, LUAN SOARES DE - ICMC
- Unidade: ICMC
- DOI: 10.1145/3539637.3557002
- Subjects: MINERAÇÃO DE DADOS; RECONHECIMENTO DE TEXTO; MULTIMÍDIA INTERATIVA
- Keywords: hierarchical clustering; multi-level summarization
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Proceedings
- Conference titles: Brazilian Symposium on Multimedia and the Web - WebMedia
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
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ABNT
SOUZA, Luan Soares de e MANZATO, Marcelo Garcia. Aspect-based summarization: an approach with different levels of details to explain recommendations. 2022, Anais.. New York: ACM, 2022. Disponível em: https://doi.org/10.1145/3539637.3557002. Acesso em: 15 fev. 2026. -
APA
Souza, L. S. de, & Manzato, M. G. (2022). Aspect-based summarization: an approach with different levels of details to explain recommendations. In Proceedings. New York: ACM. doi:10.1145/3539637.3557002 -
NLM
Souza LS de, Manzato MG. Aspect-based summarization: an approach with different levels of details to explain recommendations [Internet]. Proceedings. 2022 ;[citado 2026 fev. 15 ] Available from: https://doi.org/10.1145/3539637.3557002 -
Vancouver
Souza LS de, Manzato MG. Aspect-based summarization: an approach with different levels of details to explain recommendations [Internet]. Proceedings. 2022 ;[citado 2026 fev. 15 ] Available from: https://doi.org/10.1145/3539637.3557002 - A user study on explanations with different levels of detail in recommender systems
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- gSVD++: supporting implicit feedback on recommender systems with metadata awareness
- A collaborative filtering approach based on user's reviews
- Multimodal interactions in recommender systems: an ensembling approach
Informações sobre o DOI: 10.1145/3539637.3557002 (Fonte: oaDOI API)
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