Arthur F. Da Costa

According to our database, Arthur F. Da Costa authored at least 19 papers between 2014 and 2020.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2020

Pre-processing approaches for collaborative filtering based on hierarchical clustering.

Fernando Soares de Aguiar Neto, Arthur F. Da Costa, Marcelo G. Manzato, Ricardo J. G. B. Campello

Inf. Sci., 2020

2019

Boosting collaborative filtering with an ensemble of co-trained recommenders.

Arthur F. Da Costa, Marcelo G. Manzato, Ricardo J. G. B. Campello

Expert Syst. Appl., 2019

A personalized clustering-based approach using open linked data for search space reduction in recommender systems.

Arthur F. Da Costa, Rafael Martins D'Addio, Eduardo P. Fressato, Marcelo G. Manzato

Proceedings of the 25th Brazillian Symposium on Multimedia and the Web, 2019

2018

Enhancing Spatial Keyword Preference Query with Linked Open Data.

João Paulo Dias de Almeida, Frederico Araújo Durão, Arthur Fortes da Costa

J. Univers. Comput. Sci., 2018

CoBaR: Confidence-Based Recommender.

Fernando Soares de Aguiar Neto, Arthur F. Da Costa, Marcelo G. Manzato

CoRR, 2018

Incorporating Semantic Item Representations to Soften the Cold Start Problem.

Rafael Martins D'Addio, Eduardo P. Fressato, Arthur F. Da Costa, Marcelo G. Manzato

Proceedings of the 24th Brazilian Symposium on Multimedia and the Web, 2018

Evaluating Multiple User Interactions for Ranking Personalization Using Ensemble Methods.

Frederico Araújo Durão, Bruno Souza Cabral, Marcelo G. Manzato, Arthur F. Da Costa

Proceedings of the 30th International Conference on Software Engineering and Knowledge Engineering, 2018

CoRec: a co-training approach for recommender systems.

Arthur F. Da Costa, Marcelo G. Manzato, Ricardo J. G. B. Campello

Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 2018

Case recommender: a flexible and extensible python framework for recommender systems.

Arthur F. Da Costa, Eduardo P. Fressato, Fernando Soares de Aguiar Neto, Marcelo G. Manzato, Ricardo J. G. B. Campello

Proceedings of the 12th ACM Conference on Recommender Systems, 2018

Similarity-Based Matrix Factorization for Item Cold-Start in Recommender Systems.

Eduardo Pereira Fressato, Arthur Fortes da Costa, Marcelo Garcia Manzato

Proceedings of the 7th Brazilian Conference on Intelligent Systems, 2018

2017

Ensemble Clustering Approaches Applied in Group-based Collaborative Filtering Supported by Multiple Users' Feedback.

Arthur F. Da Costa, Marcelo G. Manzato, Ricardo J. G. B. Campello

J. Inf. Data Manag., 2017

2016

Exploiting multimodal interactions in recommender systems with ensemble algorithms.

Arthur F. Da Costa, Marcelo G. Manzato

Inf. Syst., 2016

Mining unstructured content for recommender systems: an ensemble approach.

Marcelo G. Manzato, Marcos Aurélio Domingues, Arthur da Costa Fortes, Camila Vaccari Sundermann, Rafael Martins D'Addio, Merley da Silva Conrado, Solange O. Rezende, Maria G. C. Pimentel

Inf. Retr. J., 2016

Group-based Collaborative Filtering Supported by Multiple Users' Feedback to Improve Personalized Ranking.

Arthur F. Da Costa, Marcelo G. Manzato, Ricardo J. G. B. Campello

Proceedings of the 22nd Brazilian Symposium on Multimedia and the Web, 2016

Exploiting different users' interactions for profiles enrichment in recommender systems.

Arthur F. Da Costa, Rafael D. Martins, Marcelo G. Manzato, Ricardo J. G. B. Campello

Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

2015

Introducing the concept of "always-welcome recommendations".

Edson B. dos Santos, Arthur F. Da Costa, Rafael Martins D'Addio, Marcelo Garcia Manzato, Rudinei Goularte

Proceedings of the 14th IEEE/ACIS International Conference on Computer and Information Science, 2015

2014

Ensemble Learning in Recommender Systems: Combining Multiple User Interactions for Ranking Personalization.

Arthur da Costa Fortes, Marcelo Garcia Manzato

Proceedings of the 20th Brazilian Symposium on Multimedia and the Web, 2014

Improving Personalized Ranking in Recommender Systems with Multimodal Interactions.

Arthur F. Da Costa, Marcos Aurélio Domingues, Solange Oliveira Rezende, Marcelo G. Manzato

Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Warsaw, Poland, August 11-14, 2014, 2014

Multimodal Interactions in Recommender Systems: An Ensembling Approach.

Arthur da Costa Fortes, Marcelo Garcia Manzato

Proceedings of the 2014 Brazilian Conference on Intelligent Systems, 2014