A user study with aspect-based sentiment analysis for similarity of items in content-based recommendations (2022)
- Authors:
- USP affiliated authors: MANZATO, MARCELO GARCIA - ICMC ; PRESSATO, DIANY - ICMC ; ZANON, ANDRE LEVI - ICMC ; SOUZA, LUAN SOARES DE - ICMC
- Unidade: ICMC
- DOI: 10.1111/exsy.12991
- Subjects: PROCESSAMENTO DE LINGUAGEM NATURAL; RECONHECIMENTO DE TEXTO; ALGORITMOS ÚTEIS E ESPECÍFICOS
- Keywords: content-based; recommender systems; explanation; recommender systems; sentiment analysis
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Expert Systems
- ISSN: 0266-4720
- Volume/Número/Paginação/Ano: v. 39, n. 8, p. 1-15, Sep. 2022
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
ZANON, André Levi et al. A user study with aspect-based sentiment analysis for similarity of items in content-based recommendations. Expert Systems, v. 39, n. 8, p. Se 2022, 2022Tradução . . Disponível em: https://doi.org/10.1111/exsy.12991. Acesso em: 20 maio 2024. -
APA
Zanon, A. L., Souza, L. S. de, Pressato, D., & Manzato, M. G. (2022). A user study with aspect-based sentiment analysis for similarity of items in content-based recommendations. Expert Systems, 39( 8), Se 2022. doi:10.1111/exsy.12991 -
NLM
Zanon AL, Souza LS de, Pressato D, Manzato MG. A user study with aspect-based sentiment analysis for similarity of items in content-based recommendations [Internet]. Expert Systems. 2022 ; 39( 8): Se 2022.[citado 2024 maio 20 ] Available from: https://doi.org/10.1111/exsy.12991 -
Vancouver
Zanon AL, Souza LS de, Pressato D, Manzato MG. A user study with aspect-based sentiment analysis for similarity of items in content-based recommendations [Internet]. Expert Systems. 2022 ; 39( 8): Se 2022.[citado 2024 maio 20 ] Available from: https://doi.org/10.1111/exsy.12991 - WordRecommender: an explainable content-based algorithm based on sentiment analysis and semantic similarity
- A multiturn recommender system with explanations
- Aspect-based summarization: an approach with different levels of details to explain recommendations
- A user study on explanations with different levels of detail in recommender systems
- Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open Data
- Personalizing explanations in recommender systems with different levels of details based on users\' reviews
- Incorporating semantic item representations to soften the cold start problem
- Uma arquitetura de personalização de conteúdo baseada em anotações do usuário
- gSVD++: supporting implicit feedback on recommender systems with metadata awareness
- Metadata in movies recommendation: a comparison among different approaches
Informações sobre o DOI: 10.1111/exsy.12991 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 | 3074422.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
