Obserwuj
Arthur Fortes da Costa
Arthur Fortes da Costa
Cellere
Zweryfikowany adres z cellereit.com.br
Tytuł
Cytowane przez
Cytowane przez
Rok
Exploiting multimodal interactions in recommender systems with ensemble algorithms
AF Da Costa, MG Manzato
Information Systems 56, 120-132, 2016
342016
Case recommender: a flexible and extensible python framework for recommender systems
A Da Costa, E Fressato, F Neto, M Manzato, R Campello
Proceedings of the 12th ACM Conference on Recommender Systems, 494-495, 2018
262018
Ensemble learning in recommender systems: Combining multiple user interactions for ranking personalization
A da Costa Fortes, MG Manzato
Proceedings of the 20th Brazilian Symposium on Multimedia and the Web, 47-54, 2014
232014
Boosting collaborative filtering with an ensemble of co-trained recommenders
AF Da Costa, MG Manzato, RJGB Campello
Expert Systems with Applications 115, 427-441, 2019
192019
Pre-processing approaches for collaborative filtering based on hierarchical clustering
FS de Aguiar Neto, AF Da Costa, MG Manzato, RJGB Campello
Information Sciences 534, 172-191, 2020
162020
Mining unstructured content for recommender systems: an ensemble approach
MG Manzato, MA Domingues, AC Fortes, CV Sundermann, RM D’Addio, ...
Information Retrieval Journal 19, 378-415, 2016
152016
Group-based collaborative filtering supported by multiple users' feedback to improve personalized ranking
AF Da Costa, MG Manzato, RJGB Campello
Proceedings of the 22nd Brazilian Symposium on Multimedia and the Web, 279-286, 2016
92016
CoRec: a co-training approach for recommender systems
AF Da Costa, MG Manzato, RJGB Campello
Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 696-703, 2018
82018
Multimodal interactions in recommender systems: An ensembling approach
AF Da Costa, MG Manzato
2014 Brazilian Conference on Intelligent Systems, 67-72, 2014
62014
Pre-processing approaches for collaborative filtering based on hierarchical clustering
FSA Neto, AFD Costa, MG Manzato, R Campello
Inf. Sci 534, 172-191, 2020
52020
Similarity-based matrix factorization for item cold-start in recommender systems
EP Fressato, AF da Costa, MG Manzato
2018 7th Brazilian Conference on Intelligent Systems (BRACIS), 342-347, 2018
52018
Incorporating semantic item representations to soften the cold start problem
RM D'Addio, EP Fressato, AF Da Costa, MG Manzato
Proceedings of the 24th Brazilian Symposium on Multimedia and the Web, 157-164, 2018
52018
Case recommender: A recommender framework
AF da Costa, MG Manzato
Anais Estendidos do XXII Simpósio Brasileiro de Sistemas Multimídia e Web …, 2016
52016
Improving personalized ranking in recommender systems with multimodal interactions
AF Da Costa, MA Domingues, SO Rezende, MG Manzato
2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI …, 2014
42014
Enhancing spatial keyword preference query with linked open data
JP Dias de Almeida, FA Durão, AF da Costa
Journal of Universal Computer Science 24 (11), 1561-1581, 2018
32018
Introducing the concept of “always-welcome recommendations”
EB dos Santos, AF Da Costa, RM D'addio, MG Manzato, R Goularte
2015 IEEE/ACIS 14th International Conference on Computer and Information …, 2015
22015
A personalized clustering-based approach using open linked data for search space reduction in recommender systems
AF Costa, RM D'Addio, EP Fressato, MG Manzato
Proceedings of the 25th Brazillian Symposium on Multimedia and the Web, 409-416, 2019
12019
Cobar: Confidence-based recommender
FSA Neto, AF da Costa, MG Manzato
arXiv preprint arXiv:1808.07089, 2018
12018
CoBaR: Confidence-Based Recommender
FS Aguiar Neto, AF Da Costa, MG Manzato
arXiv e-prints, arXiv: 1808.07089, 2018
2018
Evaluating Multiple User Interactions for Ranking Personalization Using Ensemble Methods.
FA Durao, BS Cabral, MG Manzato, AF Da Costa
SEKE, 697-696, 2018
2018
Nie można teraz wykonać tej operacji. Spróbuj ponownie później.
Prace 1–20