A. Plastino

发表

MIC 2003 : The Fifth Metaheuristics International Conference ? ?-1 GRASP for the maximum diversity problem

S. Martins, P. M. F. Andrade, A. Plastino, 2005 .

An E ective Strategy for Feature Selection in High-Dimensional Datasets

C. Ribeiro, B. Zadrozny, A. Plastino, 2016 .

Combining classification and regression for improving permeability estimations from 1H NMR relaxation data

Eduardo Corrêa Gonçalves, A. Plastino, R. B. V. Azeredo, 2017 .

DMC-GRASP: A Continuous GRASP hybridized with Data Mining

A. Plastino, A. Oliveira, Raphael Gomes Santos, 2022, 2022 IEEE Congress on Evolutionary Computation (CEC).

A Provenance-based Execution Strategy for Variant GPU-accelerated Scientific Workflows in Clouds

Murilo B. Stockinger, Isabel Rosseti, A. Plastino, 2022, Journal of Grid Computing.

Adaptive and multi-mining versions of the DM-GRASP hybrid metaheuristic

Luis Filipe M. Santos, S. Martins, A. Plastino, 2013, Journal of Heuristics.

On the evaluation and combination of state-of-the-art features in Twitter sentiment analysis

Alexandre Plastino, Jonnathan Carvalho, A. Plastino, 2020, Artificial Intelligence Review.

Correlation analysis of performance measures for multi-label classification

Bianca Zadrozny, Luiz Henrique de Campos Merschmann, Alexandre Plastino, 2018, Inf. Process. Manag..

Is p-value $<$ 0.05 enough? A study on the statistical evaluation of classifiers

Alex A. Freitas, Nadine M. Neumann, Alexandre Plastino, 2020, Knowledge engineering review (Print).

Prioritizing positive feature values: a new hierarchical feature selection method

Alexandre Plastino, Pablo Nascimento da Silva, Alex A. Freitas, 2020, Applied Intelligence.

A Novel Feature Selection Method for Uncertain Features: An Application to the Prediction of Pro-/Anti-Longevity Genes

Alexandre Plastino, Fabio Fabris, Pablo Nascimento Da Silva, 2020, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

A Novel Genetic Algorithm for Feature Selection in Hierarchical Feature Spaces

Alex Alves Freitas, Alexandre Plastino, Pablo Nascimento da Silva, 2018, SDM.

Interpretable Ensembles of Classifiers for Uncertain Data With Bioinformatics Applications

J. de Magalhães, M. R. Maia, A. Plastino, 2022, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

An Ensemble of Naive Bayes Classifiers for Uncertain Categorical Data

A. Freitas, M. R. Maia, A. Plastino, 2021, 2021 IEEE International Conference on Data Mining (ICDM).

A provenance-based heuristic for preserving results confidentiality in cloud-based scientific workflows

Isabel Rosseti, Daniel de Oliveira, Luidi Simonetti, 2019, Future Gener. Comput. Syst..

Evaluating a Scientific SPMD Application on a Computational Grid with Different Load Balancing Techniques

Alexandre Plastino, Simone L. Martins, André Oliveira, 2005, ISSADS.

GRASP with Path-Relinking for the Maximum Diversity Problem

Alexandre Plastino, Simone L. Martins, Marcos R. Q. de Andrade, 2005, WEA.

Hybrid data mining heuristics for the heterogeneous fleet vehicle routing problem

Puca Huachi Vaz Penna, Alexandre Plastino, Marcelo Rodrigues de Holanda Maia, 2018, RAIRO Oper. Res..

Prediction of carbonate rock type from NMR responses using data mining techniques

Alexandre Plastino, Eduardo Corrêa Gonçalves, Pablo Nascimento da Silva, 2017 .

A data mining approach for automatic classification of rock permeability

Eduardo Corrêa Gonçalves, Edmilson Helton Rios, A. Plastino, 2021, Journal of Applied Geophysics.

Automatic classification of carbonate rocks permeability from 1H NMR relaxation data

Alexandre Plastino, Asif Muhammad, Eduardo Corrêa Gonçalves, 2015, Expert systems with applications.

Sentiment analysis in tweets: an assessment study from classical to modern word representation models pdf

Alexandre Plastino, Aline Paes, S'ergio Barreto, 2021, Data Mining and Knowledge Discovery.

A Survey of Genetic Algorithms for Multi-Label Classification

Alex Alves Freitas, Alexandre Plastino, Eduardo Corrêa Gonçalves, 2018, 2018 IEEE Congress on Evolutionary Computation (CEC).

Acceptance factors of pull requests in open-source projects

Leonardo Gresta Paulino Murta, Alexandre Plastino, Manoel Limeira de Lima Júnior, 2015, SAC.

Is P-value<0.05 Enough? Two Case Studies in Classifiers Evaluation

Alex A. Freitas, Alexandre Plastino, Nadine M. Neumann, 2018, Anais do XV Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2018).

New heuristics for the maximum diversity problem

Luiz Satoru Ochi, Alexandre Plastino, Simone L. Martins, 2007, J. Heuristics.

What Should I Code Now?

Leonardo Gresta Paulino Murta, Alexandre Plastino, Luiz Antonio da Ponte Junior, 2014, J. Univers. Comput. Sci..

Improving Lazy Attribute Selection

Alex Alves Freitas, Bianca Zadrozny, Luiz Henrique de Campos Merschmann, 2011, J. Inf. Data Manag..

Lazy attribute selection: Choosing attributes at classification time

Alex Alves Freitas, Bianca Zadrozny, Luiz Henrique de Campos Merschmann, 2011, Intell. Data Anal..

Exploring Attribute Selection in Hierarchical Classification

Alex Alves Freitas, Alexandre Plastino, Bruno C. Paes, 2014, J. Inf. Data Manag..

Attributes that may raise the occurrence of merge conflicts

Leonardo Murta, João Felipe Pimentel, Leonardo Gresta Paulino Murta, 2021, J. Softw. Eng. Res. Dev..

What causes merge conflicts?

Leonardo Murta, João Felipe Pimentel, Alexandre Plastino, 2020, SBES.

Automatic assignment of integrators to pull requests: The importance of selecting appropriate attributes

Leonardo Gresta Paulino Murta, Alexandre Plastino, Manoel Limeira de Lima Júnior, 2018, J. Syst. Softw..

What factors influence the reviewer assignment to pull requests?

Leonardo Gresta Paulino Murta, Alexandre Plastino, Manoel Limeira de Lima Júnior, 2018, Inf. Softw. Technol..

Developers assignment for analyzing pull requests

Leonardo Gresta Paulino Murta, Alexandre Plastino, Manoel Limeira de Lima Júnior, 2015, SAC.

A Genetic Algorithm for Optimizing the Label Ordering in Multi-label Classifier Chains

Alex Alves Freitas, Alexandre Plastino, Eduardo Corrêa Gonçalves, 2013, 2013 IEEE 25th International Conference on Tools with Artificial Intelligence.

MineReduce: an approach based on data mining for problem size reduction pdf

Puca Huachi Vaz Penna, Alexandre Plastino, Marcelo Rodrigues de Holanda Maia, 2020, Comput. Oper. Res..

A biased random-key genetic algorithm for the maximum quasi-clique problem

Celso C. Ribeiro, Bruno Q. Pinto, Isabel Rosseti, 2018, European Journal of Operational Research.

Predicting the lifetime of pull requests in open‐source projects

Leonardo Gresta Paulino Murta, Manoel Limeira de Lima Júnior, A. Plastino, 2021, J. Softw. Evol. Process..

What factors influence the lifetime of pull requests?

Leonardo Murta, Leonardo Gresta Paulino Murta, Alexandre Plastino, 2020, Softw. Pract. Exp..

A novel probabilistic Jaccard distance measure for classification of sparse and uncertain data

I. Martire, P. N. da Silva, A. Plastino, 2017 .

Distinct Chains for Different Instances: An Effective Strategy for Multi-label Classifier Chains

Alex Alves Freitas, Alexandre Plastino, Eduardo Corrêa Gonçalves, 2014, ECML/PKDD.

Improving Local Per Level Hierarchical Classification

Alex Alves Freitas, Alexandre Plastino, Bruno C. Paes, 2012, J. Inf. Data Manag..

Categorizing feature selection methods for multi-label classification

Bianca Zadrozny, Luiz Henrique de Campos Merschmann, Alexandre Plastino, 2016, Artificial Intelligence Review.

Rejection Factors of Pull Requests Filed by Core Team Developers in Software Projects with High Acceptance Rates

Leonardo Gresta Paulino Murta, Alexandre Plastino, Manoel Limeira de Lima Júnior, 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

Making a state-of-the-art heuristic faster with data mining

S. Martins, Isabel Rosseti, A. Plastino, 2014, Annals of Operations Research.

Extending the Hybridization of Metaheuristics with Data Mining to a Broader Domain

Isabel Rosseti, Alexandre Plastino, Marcos Guerine, 2014, ICEIS.

A hybrid data mining metaheuristic for the p‐median problem

Alex Alves Freitas, Saïd Salhi, Alexandre Plastino, 2011, Stat. Anal. Data Min..

Improving Direct Counting for Frequent Itemset Mining

Alexandre Plastino, Adriana Prado, Cristiane Targa, 2004, DaWaK.

Making Heuristics Faster with Data Mining

Isabel Rosseti, Alexandre Plastino, Simone L. Martins, 2012 .

A Provenance-based Execution Strategy for Variant GPU-accelerated Scientific Workflows in Clouds

Murilo B. Stockinger, Isabel Rosseti, A. Plastino, 2022, Journal of Grid Computing.

Improving a State-of-the-Art Heuristic for the Minimum Latency Problem with Data Mining pdf

Ítalo Gomes Santana, Isabel Rosseti, A. Plastino, 2018, International Transactions in Operational Research.

Making a state-of-the-art heuristic faster with data mining

Daniel Martins, Isabel Rosseti, Alexandre Plastino, 2018, Ann. Oper. Res..

A Fast and Effective Strategy for Feature Selection in High-dimensional Datasets

Celso C. Ribeiro, Bianca Zadrozny, Alexandre Plastino, 2017, J. Inf. Data Manag..

Adaptive and multi-mining versions of the DM-GRASP hybrid metaheuristic

Alexandre Plastino, Simone L. Martins, Hugo Barbalho, 2014, J. Heuristics.

A hybrid data mining GRASP with path-relinking

Isabel Rosseti, Alexandre Plastino, Simone L. Martins, 2013, Comput. Oper. Res..

Applications of the DM-GRASP heuristic: a survey

Alexandre Plastino, Simone L. Martins, Luis Filipe M. Santos, 2008, Int. Trans. Oper. Res..

NGL01-4: A Hybrid GRASP with Data Mining for Efficient Server Replication for Reliable Multicast

Alexandre Plastino, Simone L. Martins, Luis Filipe M. Santos, 2006, IEEE Globecom 2006.

Hybridization of GRASP Metaheuristic with Data Mining Techniques

Alexandre Plastino, Simone L. Martins, Marcos Henrique Ribeiro, 2006, J. Math. Model. Algorithms.

A Hybrid GRASP with Data Mining for the Maximum Diversity Problem

Alexandre Plastino, Simone L. Martins, Marcos Henrique Ribeiro, 2005, Hybrid Metaheuristics.

Data Mining in Stochastic Local Search

Isabel Rosseti, Alexandre Plastino, Simone de Lima Martins, 2018, Handbook of Heuristics.

Extending the hybridization of metaheuristics with data mining: Dealing with sequences

Isabel Rosseti, Alexandre Plastino, Marcos Guerine, 2016, Intell. Data Anal..

Do code refactorings influence the merge effort?

Alessandro F. Garcia, Leonardo Gresta Paulino Murta, Ana Carla Bibiano, 2023, 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE).

Simpler is Better: a Novel Genetic Algorithm to Induce Compact Multi-label Chain Classifiers

Alex Alves Freitas, Alexandre Plastino, Eduardo Corrêa Gonçalves, 2015, GECCO.

Transfer learning for Twitter sentiment analysis: Choosing an effective source dataset

A. Plastino, A. Paes, Jonnathan Carvalho, 2020 .

Recruiting from the Network: Discovering Twitter Users Who Can Help Combat Zika Epidemics

Alessandro F. Garcia, Paolo Missier, Alexander Romanovsky, 2017, ICWE.

Developing SPMD applications with load balancing

Celso C. Ribeiro, Noemi de La Rocque Rodriguez, Alexandre Plastino, 2003, Parallel Comput..

A framework for SPMD applications with load balancing

C. Ribeiro, A. Plastino, N. Rodriguez, 2007 .

A Statistical and Evolutionary Approach to Sentiment Analysis

Alexandre Plastino, Adriana Prado, Jonnathan Carvalho, 2014, 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT).

Sequential coding patterns: How to use them effectively in code recommendation

Leonardo Murta, Leonardo Gresta Paulino Murta, Alexandre Plastino, 2021, Inf. Softw. Technol..

Vertical Code Completion: Going Beyond the Current Ctrl+Space

Leonardo Gresta Paulino Murta, Alexandre Plastino, Luiz Laerte Nunes da Silva, 2012, 2012 Sixth Brazilian Symposium on Software Components, Architectures and Reuse.