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Refinado por: autor: Manzato, M remover
Result Number Material Type Add to My Shelf Action Record Details and Options
1
Aspect-based summarization an approach with different levels of details to explain recommendations
Aspect-based summarization an approach with different levels of details to explain recommendations
Material Type:
Artigo de Congresso 		Adicionar ao Meu Espaço

Aspect-based summarization an approach with different levels of details to explain recommendations

Luan Soares de Souza Marcelo Garcia Manzato; Brazilian Symposium on Multimedia and the Web - WebMedia (28. 2022 Curitiba)

Proceedings New York : ACM, 2022

New York ACM 2022

Localização: ICMC - Inst. Ciên. Mat. Computação    (PROD-3105452 )(Acessar)

2
Exploiting feature extraction techniques on users' reviews for movies recommendation
Exploiting feature extraction techniques on users' reviews for movies recommendation
Material Type:
Artigo 		Adicionar ao Meu Espaço

Exploiting feature extraction techniques on users' reviews for movies recommendation

Rafael M D'Addio Marcos A Domingues; Marcelo Garcia Manzato

Journal of the Brazilian Computer Society Heidelberg : SpringerOpen v. 23, p. 1-16, 2017

Heidelberg 2017

Localização: ICMC - Inst. Ciên. Mat. Computação    (PROD-2839045 )(Acessar)

3
Combining different metadata views for better recommendation accuracy
Combining different metadata views for better recommendation accuracy
Material Type:
Artigo 		Adicionar ao Meu Espaço

Combining different metadata views for better recommendation accuracy

Rafael Martins D'Addio Ronnie Shida Marinho; Marcelo Garcia Manzato

Information Systems Kidlington : Pergamon : Elsevier v. 83, p. 1-12, July 2019

Kidlington 2019

Localização: ICMC - Inst. Ciên. Mat. Computação    (PROD-2933876 )(Acessar)

4
A user study with aspect-based sentiment analysis for similarity of items in content-based recommendations
A user study with aspect-based sentiment analysis for similarity of items in content-based recommendations
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A user study with aspect-based sentiment analysis for similarity of items in content-based recommendations

André Levi Zanon Luan Soares de Souza; Diany Pressato; Marcelo Garcia Manzato

Expert Systems Hoboken v. 39, n. 8, p. 1-15, Sep. 2022

Hoboken 2022

Localização: ICMC - Inst. Ciên. Mat. Computação    (PROD-3074422 )(Acessar)

5
Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open Data
Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open Data
Material Type:
Artigo 		Adicionar ao Meu Espaço

Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open Data

André Levi Zanon Leonardo Chaves Dutra da Rocha; Marcelo Garcia Manzato

Knowledge-Based Systems Amsterdam v. 252, p. 1-19, Sep. 2022

Amsterdam 2022

Localização: ICMC - Inst. Ciên. Mat. Computação    (PROD-3090220 )(Acessar)

6
Semantic organization of user's reviews applied in recommender systems
Semantic organization of user's reviews applied in recommender systems
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Artigo de Congresso 		Adicionar ao Meu Espaço

Semantic organization of user's reviews applied in recommender systems

Ronnei S Marinho Rafael M D'Addio; Marcelo Garcia Manzato; Brazilian Symposium on Multimedia and the Web - WebMedia (23. 2017 Gramado)

Proceedings New York : ACM, 2017

New York ACM 2017

Localização: ICMC - Inst. Ciên. Mat. Computação    (PROD-2858736 )(Acessar)

7
WordRecommender an explainable content-based algorithm based on sentiment analysis and semantic similarity
WordRecommender an explainable content-based algorithm based on sentiment analysis and semantic similarity
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Artigo de Congresso 		Adicionar ao Meu Espaço

WordRecommender an explainable content-based algorithm based on sentiment analysis and semantic similarity

André Levi Zanon Luan Soares de Souza; Diany Pressato; Marcelo Garcia Manzato; Brazilian Symposium on Multimedia and the Web - WebMedia (26. 2020 São Luís)

Proceedings New York : ACM, 2020

New York ACM 2020

Localização: ICMC - Inst. Ciên. Mat. Computação    (PROD-3011659 )(Acessar)

8
Mining unstructured content for recommender systems an ensemble approach
Mining unstructured content for recommender systems an ensemble approach
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Mining unstructured content for recommender systems an ensemble approach

Marcelo Garcia Manzato Marcos A Domingues; Arthur C Fortes; Camila V Sundermann; Rafael M D'Addio; Merley S Conrado; Solange Oliveira Rezende; Maria da Graça Campos Pimentel

Information Retrieval Journal Dordrecht : Springer v. 19, n. 4, p. 378-415, Aug. 2016

Dordrecht 2016

Localização: ICMC - Inst. Ciên. Mat. Computação    (PROD-2763540 )(Acessar)

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