Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open Data (2022)
- Authors:
- USP affiliated authors: MANZATO, MARCELO GARCIA - ICMC ; ZANON, ANDRE LEVI - ICMC
- Unidade: ICMC
- DOI: 10.1016/j.knosys.2022.109333
- Subjects: RECONHECIMENTO DE TEXTO; ALGORITMOS ÚTEIS E ESPECÍFICOS; WEB SEMÂNTICA
- Keywords: Recommender systems; Collaborative filtering; Linked open data; Explainable AI
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Knowledge-Based Systems
- ISSN: 0950-7051
- Volume/Número/Paginação/Ano: v. 252, p. 1-19, Sep. 2022
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
ZANON, André Levi e ROCHA, Leonardo Chaves Dutra da e MANZATO, Marcelo Garcia. Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open Data. Knowledge-Based Systems, v. 252, p. Se 2022, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.knosys.2022.109333. Acesso em: 15 fev. 2026. -
APA
Zanon, A. L., Rocha, L. C. D. da, & Manzato, M. G. (2022). Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open Data. Knowledge-Based Systems, 252, Se 2022. doi:10.1016/j.knosys.2022.109333 -
NLM
Zanon AL, Rocha LCD da, Manzato MG. Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open Data [Internet]. Knowledge-Based Systems. 2022 ; 252 Se 2022.[citado 2026 fev. 15 ] Available from: https://doi.org/10.1016/j.knosys.2022.109333 -
Vancouver
Zanon AL, Rocha LCD da, Manzato MG. Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open Data [Internet]. Knowledge-Based Systems. 2022 ; 252 Se 2022.[citado 2026 fev. 15 ] Available from: https://doi.org/10.1016/j.knosys.2022.109333 - O impacto de estratégias de embeddings de grafos na explicabilidade de sistemas de recomendação
- Model-agnostic knowledge graph embedding explanations for recommender systems
- An exploration of recommender systems explanation paradigms: generating and evaluating syntactic, semantic, and generative models with knowledge graphs
- A user study with aspect-based sentiment analysis for similarity of items in content-based recommendations
- A multiturn recommender system with explanations
- WordRecommender: an explainable content-based algorithm based on sentiment analysis and semantic similarity
- Metadata in movies recommendation: a comparison among different approaches
- 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: 10.1016/j.knosys.2022.109333 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
3090220.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
