Ricardo Bastos Cavalcante Prudêncio

Ricardo B. C. Prudêncio

	2013
j9		Luciano S. de Souza, Ricardo B. C. Prudêncio, Flávia de Almeida Barros, Eduardo Henrique da Silva Aranha: Search based constrained test case selection using execution effort. Expert Syst. Appl. 40(12): 4887-4896 (2013)
	2012
j8		Taciana A. F. Gomes, Ricardo Bastos Cavalcante Prudêncio, Carlos Soares, André L. D. Rossi, André C. P. L. F. Carvalho: Combining meta-learning and search techniques to select parameters for support vector machines. Neurocomputing 75(1): 3-13 (2012)
j7		Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir: Combining Uncertainty Sampling methods for supporting the generation of meta-examples. Inf. Sci. 196: 1-14 (2012)
c38		Péricles B. C. de Miranda, Ricardo Bastos Cavalcante Prudêncio, André Carlos Ponce Leon Ferreira de Carvalho, Carlos Soares: An Experimental Study of the Combination of Meta-Learning with Particle Swarm Algorithms for SVM Parameter Selection. ICCSA (3) 2012: 562-575
c37		Juliano C. B. Rabelo, Ricardo B. C. Prudêncio, Flávia A. Barros: Collective Classification for Sentiment Analysis in Social Networks. ICTAI 2012: 958-963
c36		Péricles B. C. de Miranda, Ricardo Bastos Cavalcante Prudêncio, André Carlos Ponce Leon Ferreira de Carvalho, Carlos Soares: Multi-objective optimization and Meta-learning for SVM parameter selection. IJCNN 2012: 1-8
c35		Paulo Ricardo da Silva Soares, Ricardo Bastos Cavalcante Prudêncio: Time Series Based Link Prediction. IJCNN 2012: 1-7
c34		Péricles B. C. de Miranda, Ricardo B. C. Prudêncio, André C. P. L. F. Carvalho, Carlos Soares: Combining Meta-Learning with Multi-objective Particle Swarm Algorithms for SVM Parameter Selection: An Experimental Analysis. SBRN 2012: 1-6
c33		Juliano C. B. Rabelo, Ricardo B. C. Prudêncio, Flávia de Almeida Barros: Using link structure to infer opinions in social networks. SMC 2012: 681-685
c32		Péricles B. C. de Miranda, Ricardo Bastos Cavalcante Prudêncio, André Carlos Ponce Leon Ferreira de Carvalho, Carlos Soares: Combining a multi-objective optimization approach with meta-learning for SVM parameter selection. SMC 2012: 2909-2914
c31		Juliano C. B. Rabelo, Ricardo B. C. Prudêncio, Flávia A. Barros: Leveraging relationships in social networks for sentiment analysis. WebMedia 2012: 181-188
	2011
j6		Teresa Bernarda Ludermir, Ricardo Bastos Cavalcante Prudêncio, Cleber Zanchettin: Feature and algorithm selection with Hybrid Intelligent Techniques. Int. J. Hybrid Intell. Syst. 8(3): 115-116 (2011)
c30		Ricardo Bastos Cavalcante Prudêncio, Carlos Soares, Teresa Bernarda Ludermir: Combining Meta-learning and Active Selection of Datasetoids for Algorithm Selection. HAIS (1) 2011: 164-171
c29		Ricardo Bastos Cavalcante Prudêncio, Carlos Soares, Teresa Bernarda Ludermir: Uncertainty Sampling-Based Active Selection of Datasetoids for Meta-learning. ICANN (2) 2011: 454-461
c28		Diana C. Cavalcanti, Ricardo Bastos Cavalcante Prudêncio, Shreyasee S. Pradhan, Jatin Shah, Ricardo Pietrobon: Good to be Bad? Distinguishing between Positive and Negative Citations in Scientific Impact. ICTAI 2011: 156-162
c27		Luciano S. de Souza, Péricles B. C. de Miranda, Ricardo Bastos Cavalcante Prudêncio, Flávia de Almeida Barros: A Multi-objective Particle Swarm Optimization for Test Case Selection Based on Functional Requirements Coverage and Execution Effort. ICTAI 2011: 245-252
c26		Ricardo Bastos Cavalcante Prudêncio, Carlos Soares, Teresa Bernarda Ludermir: Uncertainty sampling methods for selecting datasets in active meta-learning. IJCNN 2011: 1082-1089
c25		Hially Rodrigues de Sa, Ricardo Bastos Cavalcante Prudêncio: Supervised link prediction in weighted networks. IJCNN 2011: 2281-2288
p1		Ricardo Bastos Cavalcante Prudêncio, Marcilio C. P. de Souto, Teresa Bernarda Ludermir: Selecting Machine Learning Algorithms Using the Ranking Meta-Learning Approach. Meta-Learning in Computational Intelligence 2011: 225-243
	2010
j5		Mitsuo Takaki, Diego Cavalcanti, Rohit Gheyi, Juliano Iyoda, Marcelo d'Amorim, Ricardo Bastos Cavalcante Prudêncio: Randomized constraint solvers: a comparative study. ISSE 6(3): 243-253 (2010)
c24		Marcelo Nunes Ribeiro, Ricardo Bastos Cavalcante Prudêncio: Local Feature Selection for Generation of Ensembles in Text Clustering. SBRN 2010: 67-72
c23		Taciana A. F. Gomes, Ricardo Bastos Cavalcante Prudêncio, Carlos Soares, André L. D. Rossi, André Carlos Ponce Leon Ferreira de Carvalho: Combining Meta-learning and Search Techniques to SVM Parameter Selection. SBRN 2010: 79-84
c22		Luciano S. de Souza, Ricardo Bastos Cavalcante Prudêncio, Flávia de Almeida Barros: A Constrained Particle Swarm Optimization Approach for Test Case Selection. SEKE 2010: 259-264
	2009
j4		Flávia A. Barros, Eduardo F. A. Silva, Ricardo Bastos Cavalcante Prudêncio, Valmir M. Filho, André C. A. Nascimento: Combining Text Classifiers and Hidden Markov Models for Information Extraction. International Journal on Artificial Intelligence Tools 18(2): 311-329 (2009)
c21		André C. A. Nascimento, Ricardo Bastos Cavalcante Prudêncio, Marcílio Carlos Pereira de Souto, Ivan G. Costa: Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data. ICANN (2) 2009: 20-29
c20		Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir: Active Generation of Training Examples in Meta-Regression. ICANN (1) 2009: 30-39
c19		Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir: Combining Uncertainty Sampling Methods for Active Meta-Learning. ISDA 2009: 220-225
c18		Mitsuo Takaki, Diego Cavalcanti, Rohit Gheyi, Juliano Iyoda, Marcelo d'Amorim, Ricardo Bastos Cavalcante Prudêncio: A Comparative Study of Randomized Constraint Solvers for Random-Symbolic Testing. NASA Formal Methods 2009: 56-65
	2008
j3		Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir: Selective generation of training examples in active meta-learning. Int. J. Hybrid Intell. Syst. 5(2): 59-70 (2008)
c17		Flávia A. Barros, Eduardo F. A. Silva, Ricardo Bastos Cavalcante Prudêncio, Valmir M. Filho, André C. A. Nascimento: Hidden Markov Models and Text Classifiers for Information Extraction on Semi-Structured Texts. HIS 2008: 417-422
c16		Silvio B. Guerra, Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir: Predicting the Performance of Learning Algorithms Using Support Vector Machines as Meta-regressors. ICANN (1) 2008: 523-532
c15		Marcelo Nunes Ribeiro, Manoel J. R. Neto, Ricardo Bastos Cavalcante Prudêncio: Local Feature Selection in Text Clustering. ICONIP (2) 2008: 45-52
c14		Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir: Active Meta-Learning with Uncertainty Sampling and Outlier Detection. IJCNN 2008: 346-351
c13		Marcílio Carlos Pereira de Souto, Ricardo Bastos Cavalcante Prudêncio, Rodrigo G. F. Soares, Daniel S. A. de Araujo, Ivan G. Costa, Teresa Bernarda Ludermir, Alexander Schliep: Ranking and selecting clustering algorithms using a meta-learning approach. IJCNN 2008: 3729-3735
c12		Valmir Macário Filho, Ricardo Bastos Cavalcante Prudêncio, Francisco de A. T. de Carvalho, Leandro R. Torres, Laerte Rodrigues Jr., Marcos G. Lima: Automatic Information Extraction in Semi-structured Official Journals. SBRN 2008: 51-56
c11		Patrícia M. Santos, Teresa Bernarda Ludermir, Ricardo Bastos Cavalcante Prudêncio: Selecting Neural Network Forecasting Models Using the Zoomed-Ranking Approach. SBRN 2008: 165-170
c10		Ricardo Bastos Cavalcante Prudêncio, Silvio B. Guerra, Teresa Bernarda Ludermir: Using Support Vector Machines to Predict the Performance of MLP Neural Networks. SBRN 2008: 201-206
	2007
c9		Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir: Active Selection of Training Examples for Meta-Learning. HIS 2007: 126-131
c8		Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir: Active Learning to Support the Generation of Meta-examples. ICANN (1) 2007: 817-826
	2006
c7		Eduardo F. A. Silva, Flávia A. Barros, Ricardo Bastos Cavalcante Prudêncio: A Hybrid Machine Learning Approach for Information Extraction. HIS 2006: 44
c6		Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir: A Machine Learning Approach to Define Weights for Linear Combination of Forecasts. ICANN (1) 2006: 274-283
c5		Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir: LearningWeights for Linear Combination of Forecasting Methods. SBRN 2006: 113-118
	2004
j2		Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir: Meta-learning approaches to selecting time series models. Neurocomputing 61: 121-137 (2004)
j1		Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir, Francisco de A. T. de Carvalho: A Modal Symbolic Classifier for selecting time series models. Pattern Recognition Letters 25(8): 911-921 (2004)
c4		Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir: Using Machine Learning Techniques to Combine Forecasting Methods. Australian Conference on Artificial Intelligence 2004: 1122-1127
c3		Patrícia Maforte dos Santos, Teresa Bernarda Ludermir, Ricardo Bastos Cavalcante Prudêncio: Selection of Time Series Forecasting Models based on Performance Information. HIS 2004: 366-371
	2003
c2		Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir: Selecting and Ranking Time Series Models Using the NOEMON Approach. ICANN 2003: 654-661
	2002
c1		Ricardo Bastos Cavalcante Prudêncio, Teresa Bernarda Ludermir: Selection of Models for Time Series Prediction via Meta-Learning. HIS 2002: 74-83

Coauthor Index

Colors in the list of coauthors

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