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ORCIDAline Paes
Aline Marins Paes – Aline Marins Paes Carvalho
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- affiliation: Fluminense Federal University, Brazil
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2020 – today
- 2025
[j26]Sidney Araujo Melo
, Leonardo Thurler, Aline Paes, Esteban Clua:
Game provenance graph-based representation learning vs metrics-based machine learning: An empirical comparison on predictive game analytics tasks. Entertain. Comput. 52: 100755 (2025)- 2024
- [j25]Ricardo Moura, Jonnathan Carvalho, Alexandre Plastino, Aline Paes:
Less is more: Pruning BERTweet architecture in Twitter sentiment analysis. Inf. Process. Manag. 61(4): 103688 (2024) - [j24]Daniela Vianna, Fernando Carneiro, Jonnathan Carvalho, Alexandre Plastino, Aline Paes:
Sentiment analysis in Portuguese tweets: an evaluation of diverse word representation models. Lang. Resour. Evaluation 58(1): 223-272 (2024) - [j23]Thais Luca, Aline Paes, Gerson Zaverucha:
Word embeddings-based transfer learning for boosted relational dependency networks. Mach. Learn. 113(3): 1269-1302 (2024) - [c50]Arthur Scalercio, Maria José Finatto, Aline Paes:
Enhancing Sentence Simplification in Portuguese: Leveraging Paraphrases, Context, and Linguistic Features. ACL (Findings) 2024: 15076-15091 - [c49]João Silva-Leite, Cristina A. P. Fontes, Alair S. Santos, Diogo G. Correa, Marcel Koenigkam-Santos, Paulo M. Azevedo-Marques, Daniel de Oliveira, Aline Paes, Marcos V. N. Bedo:
Aggregating embeddings from image and radiology reports for multimodal Chest-CT retrieval. CBMS 2024: 309-314 - [c48]Elbe Miranda, Aline Paes, Daniel de Oliveira:
SPARQL can also talk in Portuguese: answering natural language questions with knowledge graphs. PROPOR 2024: 56-66 - [c47]Gabriel Assis, Annie Amorim, Jonnatahn Carvalho, Daniel de Oliveira, Daniela Q. C. Vianna, Aline Paes:
Exploring Portuguese Hate Speech Detection in Low-Resource Settings: Lightly Tuning Encoder Models or In-Context Learning of Large Models? PROPOR 2024: 301-311 - [c46]Arthur B. Vasconcelos, Luiz Felipe De Melo, Eduardo Goncalves, Eduardo Bezerra, Aline Paes, Alexandre Plastino:
BAMBAS at SemEval-2024 Task 4: How far can we get without looking at hierarchies? SemEval@NAACL 2024: 455-462 - 2023
- [j22]Sidney Araujo Melo, Luís Fernando Bicalho, Leonardo Camacho de Oliveira Joia, Jose Ricardo da Silva Junior, Esteban Clua, Aline Paes:
Encoding feature set information in heterogeneous graph neural networks for game provenance. Appl. Intell. 53(23): 29024-29042 (2023) - [j21]Sérgio Barreto, Ricardo Moura, Jonnathan Carvalho, Aline Paes, Alexandre Plastino:
Sentiment analysis in tweets: an assessment study from classical to modern word representation models. Data Min. Knowl. Discov. 37(1): 318-380 (2023) - [j20]Claudio V. Ribeiro, Aline Paes, Daniel de Oliveira:
AIS-based maritime anomaly traffic detection: A review. Expert Syst. Appl. 231: 120561 (2023) - [c45]Thais Luca, Aline Paes, Gerson Zaverucha:
Select First, Transfer Later: Choosing Proper Datasets for Statistical Relational Transfer Learning. ILP 2023: 62-76 - [c44]Bohua Peng, Chengfu Wu, Wei He, William Thorne, Aline Villavicencio, Yujin Wang, Aline Paes:
FLYPE: Multitask Prompt Tuning for Multimodal Human Understanding of Social Media. MUWS@CIKM 2023: 18-33 - [c43]Arthur B. Vasconcelos, Lúcia Maria de A. Drummond, Rafaela C. Brum, Aline Paes:
Exploring Federated Learning to Trace Depression in Social Media with Language Models. SBAC-PADW 2023: 24-30 - [i6]Daniel da Silva Junior, Paulo Roberto dos S. Corval, Aline Paes, Daniel de Oliveira:
Datasets for Portuguese Legal Semantic Textual Similarity: Comparing weak supervision and an annotation process approaches. CoRR abs/2306.00007 (2023) - 2022
- [j19]Vítor Lourenço, Aline Paes:
Learning attention-based representations from multiple patterns for relation prediction in knowledge graphs. Knowl. Based Syst. 251: 109232 (2022) - [j18]Patrick Blackman Sphaier, Aline Paes:
User intent classification in noisy texts: an investigation on neural language models. Neural Comput. Appl. 34(20): 17381-17406 (2022) - [c42]Paulo Mann, Elton H. Matsushima, Aline Paes:
Detecting Depression from Social Media Data as a Multiple-Instance Learning Task. ACII 2022: 1-8 - [c41]Jéssica Soares dos Santos, Flávia Bernardini, Aline Paes:
Similarity-Based Dataset Recommendation Across Languages and Domains to Sentiment Analysis in the Electoral Domain. ePart 2022: 107-123 - [c40]Thais Luca, Aline Paes, Gerson Zaverucha:
Combining Word Embeddings-Based Similarity Measures for Transfer Learning Across Relational Domains. ILP 2022: 84-99 - [c39]Annie Amorim, Nils Murrugarra-Llerena, Vítor Silva, Daniel de Oliveira, Aline Paes:
Modelagem de Tópicos em Textos Curtos: uma Avaliação Experimental. SBBD 2022: 254-266 - [i5]Vítor Lourenço, Aline Paes:
Learning Attention-based Representations from Multiple Patterns for Relation Prediction in Knowledge Graphs. CoRR abs/2206.04801 (2022) - [i4]Vítor Lourenço, Aline Paes:
A Modality-level Explainable Framework for Misinformation Checking in Social Networks. CoRR abs/2212.04272 (2022) - 2021
- [j17]André Nascimento, Vítor Silva, Aline Paes, Daniel de Oliveira:
An incremental reinforcement learning scheduling strategy for data-intensive scientific workflows in the cloud. Concurr. Comput. Pract. Exp. 33(11) (2021) - [j16]Maria Luiza Furtuozo Falci, Andréa Magalhães Magdaleno, Aline Paes, Vanessa Braganholo, Daniel de Oliveira:
Multimodal Provenance-based Analysis of Collaboration in Business Processes. J. Inf. Data Manag. 12(5) (2021) - [j15]Liliane N. O. Kunstmann, Débora B. Pina, Filipe Silva, Aline Paes, Patrick Valduriez, Daniel de Oliveira, Marta Mattoso:
Online Deep Learning Hyperparameter Tuning based on Provenance Analysis. J. Inf. Data Manag. 12(5) (2021) - [j14]Raphael Melo, Kate Revoredo, Aline Paes:
Learning multiple concepts in description logic through three perspectives. Knowl. Eng. Rev. 36: e8 (2021) - [j13]Daniel Silva Junior, Esther Pacitti, Aline Paes, Daniel de Oliveira:
Provenance-and machine learning-based recommendation of parameter values in scientific workflows. PeerJ Comput. Sci. 7: e606 (2021) - [j12]Sidney Loyola de Sá, Antônio A. de A. Rocha, Aline Paes:
Predicting Popularity of Video Streaming Services with Representation Learning: A Survey and a Real-World Case Study. Sensors 21(21): 7328 (2021) - [j11]Jéssica Soares dos Santos, Flávia Bernardini, Aline Paes:
A survey on the use of data and opinion mining in social media to political electoral outcomes prediction. Soc. Netw. Anal. Min. 11(1): 103 (2021) - [c38]Paulo Mann, Aline Paes, Elton H. Matsushima:
Screening for Depressed Individuals by Using Multimodal Social Media Data. AAAI 2021: 15722-15723 - [c37]Leticia Freire de Figueiredo, Aline Paes, Gerson Zaverucha:
Transfer Learning for Boosted Relational Dependency Networks Through Genetic Algorithm. ILP 2021: 125-139 - [c36]Thais Luca, Aline Paes, Gerson Zaverucha:
Mapping Across Relational Domains for Transfer Learning with Word Embeddings-Based Similarity. ILP 2021: 167-182 - [c35]Marcelo D'Almeida, Aline Paes, Daniel Mossé:
Designing Reinforcement Learning Agents for Traffic Signal Control with the Right Goals: a Time-Loss based Approach. ITSC 2021: 1412-1418 - [c34]Leonardo Thurler, José Montes, Rodrigo Veloso, Aline Paes, Esteban Clua:
AI Game Agents Based on Evolutionary Search and (Deep) Reinforcement Learning: A Practical Analysis with Flappy Bird. ICEC 2021: 196-208 - [c33]Sidney Loyola de Sá, Aline Paes, Antônio A. de A. Rocha:
Extracting Textual Features from Video Streaming Services Publications to Predict their Popularity. WebMedia 2021: 113-120 - [i3]Sérgio Barreto, Ricardo Moura, Jonnathan Carvalho, Aline Paes, Alexandre Plastino:
Sentiment analysis in tweets: an assessment study from classical to modern text representation models. CoRR abs/2105.14373 (2021) - 2020
- [j10]Pablo Carvalho, Esteban Clua, Aline Paes, Cristiana Bentes, Bruno Lopes, Lúcia Maria de A. Drummond:
Using machine learning techniques to analyze the performance of concurrent kernel execution on GPUs. Future Gener. Comput. Syst. 113: 528-540 (2020) - [j9]Rodrigo Azevedo Santos, Aline Paes, Gerson Zaverucha:
Transfer learning by mapping and revising boosted relational dependency networks. Mach. Learn. 109(7): 1435-1463 (2020) - [c32]Sidney Araujo Melo, Troy C. Kohwalter, Esteban Clua, Aline Paes, Leonardo Murta:
Player Behavior Profiling through Provenance Graphs and Representation Learning. FDG 2020: 62:1-62:11 - [c31]Paulo Mann, Aline Paes, Elton H. Matsushima:
See and Read: Detecting Depression Symptoms in Higher Education Students Using Multimodal Social Media Data. ICWSM 2020: 440-451 - [c30]Maria Luiza Furtuozo Falci, Andréa Magalhães Magdaleno, Vanessa Braganholo, Aline Paes, Daniel de Oliveira:
Análise de Colaboração em Processos de Negócio por meio de SGBDs de Grafos e Dados de Proveniência Multimodais. SBBD 2020: 169-174
2010 – 2019
- 2019
- [j8]Sidney Araujo Melo, Aline Paes, Esteban Walter Gonzalez Clua, Troy Costa Kohwalter, Leonardo Gresta Paulino Murta:
Detecting long-range cause-effect relationships in game provenance graphs with graph-based representation learning. Entertain. Comput. 32 (2019) - [j7]Fábio G. Santos, Leonardo Machado, Rafael de Araújo M. Pinheiro, Aline Paes, Vanessa Braganholo:
Querying XML documents using Prolog engines: When is this a good idea? Inf. Process. Manag. 56(5): 1753-1770 (2019) - [j6]Victor Guimarães, Aline Paes, Gerson Zaverucha:
Online probabilistic theory revision from examples with ProPPR. Mach. Learn. 108(7): 1165-1189 (2019) - [c29]José R. González, Aura Conci, Maira Beatriz Hernandez Moran, Adriel S. Araújo, Aline Paes, Charbel Damião, W. G. Fiirst:
Analysis of Static and Dynamic Infrared Images for Thyroid Nodules Investigation. AICCSA 2019: 1-7 - [c28]Jéssica Soares dos Santos, Aline Paes, Flávia Bernardini:
Combining Labeled Datasets for Sentiment Analysis from Different Domains Based on Dataset Similarity to Predict Electors Sentiment. BRACIS 2019: 455-460 - [c27]Ashey Noblega, Aline Paes, Esteban Clua:
Towards Adaptive Deep Reinforcement Game Balancing. ICAART (2) 2019: 693-700 - [c26]André Nascimento, Victor Olimpio, Vítor Silva, Aline Paes, Daniel de Oliveira:
A Reinforcement Learning Scheduling Strategy for Parallel Cloud-Based Workflows. IPDPS Workshops 2019: 817-824 - [c25]Ícaro Goulart, Aline Paes, Esteban Clua:
Learning How to Play Bomberman with Deep Reinforcement and Imitation Learning. ICEC-JCSG 2019: 121-133 - [c24]Leticia Duboc, Raquel Mendonça, Jessica Salvador, Aline Paes:
A Vision Towards a Method for Identifying and Mitigating Unsustainable Practices in Organisations. RE4SuSy@RE 2019 - [c23]Débora B. Pina, Liliane Neves, Aline Paes, Daniel de Oliveira, Marta Mattoso:
Análise de Hiperparâmetros em Aplicações de Aprendizado Profundo por meio de Dados de Proveniência. SBBD 2019: 223-228 - [i2]Paulo Mann, Aline Paes, Elton H. Matsushima:
See and Read: Detecting Depression Symptoms in Higher Education Students Using Multimodal Social Media Data. CoRR abs/1912.01131 (2019) - 2018
- [j5]Roosevelt Sardinha, Aline Paes, Gerson Zaverucha:
Revising the structure of Bayesian network classifiers in the presence of missing data. Inf. Sci. 439-440: 108-124 (2018) - [c22]Felipe Carregosa, Aline Paes, Gerson Zaverucha:
Lightweight Neural Programming: The GRPU. ICANN (3) 2018: 218-227 - [c21]Vítor Lourenço, Paulo Mann, Artur Guimaraes, Aline Paes, Daniel de Oliveira:
Towards Safer (Smart) Cities: Discovering Urban Crime Patterns Using Logic-based Relational Machine Learning. IJCNN 2018: 1-8 - [c20]Daniel Silva Jr., Aline Paes, Esther Pacitti, Daniel de Oliveira:
FReeP: towards Parameter Recommendation in Scientific Workflows using Preference Learning. SBBD 2018: 211-216 - 2017
- [j4]David B. Carvalho, Esteban Walter Gonzalez Clua, Cesar Tadeu Pozzer, Erick Baptista Passos, Aline Paes:
Simulated Perceptions for Emergent Storytelling. Comput. Intell. 33(4): 605-628 (2017) - [j3]Ana Luísa Duboc, Aline Paes, Gerson Zaverucha:
On the formal characterization of the FORTE_MBC theory revision operators. J. Log. Comput. 27(8): 2551-2580 (2017) - [j2]Aline Paes, Gerson Zaverucha, Vítor Santos Costa:
On the use of stochastic local search techniques to revise first-order logic theories from examples. Mach. Learn. 106(2): 197-241 (2017) - [c19]Marcos Kalinowski, Pablo Curty, Aline Paes, Alexandre Ferreira, Rodrigo O. Spínola, Daniel Méndez Fernández, Michael Felderer, Stefan Wagner:
Supporting Defect Causal Analysis in Practice with Cross-Company Data on Causes of Requirements Engineering Problems. ICSE-SEIP 2017: 223-232 - [i1]Marcos Kalinowski, Pablo Curty, Aline Paes, Alexandre Ferreira, Rodrigo O. Spínola, Daniel Méndez Fernández, Michael Felderer, Stefan Wagner:
Supporting Defect Causal Analysis in Practice with Cross-Company Data on Causes of Requirements Engineering Problems. CoRR abs/1702.03851 (2017) - 2016
- [c18]David B. Carvalho, Esteban Walter Gonzalez Clua, Aline Paes:
Planning social actions through the others' eyes for emergent storytelling. CIG 2016: 1-8 - [c17]Cristina Nader Vasconcelos, Aline Paes, Anselmo Antunes Montenegro:
Towards Deep Learning Invariant Pedestrian Detection by Data Enrichment. ICMLA 2016: 837-841 - [c16]Gustavo Tallarida, Kary A. C. S. Ocaña, Aline Paes, Vanessa Braganholo, Daniel de Oliveira:
Gerência de Incerteza em Bancos de Dados de Proveniência de Workflows de Bioinformática. SBBD 2016: 181-186 - [c15]Vítor N. Lourenço, Paulo Mann, Aline Paes, Daniel Oliveira:
SiAPP: Um Sistema para Análise de Ocorrências de Crimes Baseado em Aprendizado Lógico-Relacional [SiAPP: An Information System for Crime Analytics Based on Logical Relational Learning]. SBSI 2016: 168-175 - 2015
- [c14]Victor Guimarães, Aline Paes:
Looking at the Bottom and the Top: A Hybrid Logical Relational Learning System Based on Answer Sets. BRACIS 2015: 240-245 - [c13]Aline Paes, Daniel de Oliveira:
Running Multi-relational Data Mining Processes in the Cloud: A Practical Approach for Social Networks. CARLA 2015: 3-18 - [c12]David B. Carvalho, Esteban Walter Gonzalez Clua, Aline Paes:
Perception simulation in social planning for emergent storytelling. CIG 2015: 75-82 - 2014
- [c11]Raphael Melo, Kate Cerqueira Revoredo, Aline Marins Paes Carvalho:
Syntactic Compression of Description Logics Terminologies. BRACIS 2014: 180-185 - [c10]Rainier Sales, Esteban Clua, Daniel de Oliveira, Aline Paes, Luiz Chaimowicz, Maria Augusta Silveira Netto Nunes:
Evaluation between humans and affective NPC in digital gaming scenario. SeGAH 2014: 1-8 - [e2]Gerson Zaverucha, Vítor Santos Costa, Aline Marins Paes:
Late Breaking Papers of the 23rd International Conference on Inductive Logic Programming, Rio de Janeiro, Brazil, August 28th - to - 30th, 2013. CEUR Workshop Proceedings 1187, CEUR-WS.org 2014 [contents] - [e1]Gerson Zaverucha, Vítor Santos Costa, Aline Paes:
Inductive Logic Programming - 23rd International Conference, ILP 2013, Rio de Janeiro, Brazil, August 28-30, 2013, Revised Selected Papers. Lecture Notes in Computer Science 8812, Springer 2014, ISBN 978-3-662-44922-6 [contents] - 2013
- [c9]Raphael Melo, Kate Revoredo, Aline Paes:
Terminology Learning through Taxonomy Discovery. BRACIS 2013: 169-174 - [c8]Raphael Melo, Kate Revoredo, Aline Paes:
Learning Multiple Description Logics Concepts. ILP (Late Breaking Papers) 2013: 17-22 - [c7]Rainier Sales, Esteban Clua, Daniel de Oliveira, Aline Paes:
An Artificial Emotional Agent-Based Architecture for Games Simulation. ICEC 2013: 156-159
2000 – 2009
- 2009
- [j1]Ana Luísa Duboc, Aline Paes, Gerson Zaverucha:
Using the bottom clause and mode declarations in FOL theory revision from examples. Mach. Learn. 76(1): 73-107 (2009) - [c6]Stephen H. Muggleton, Aline Paes, Vítor Santos Costa, Gerson Zaverucha:
Chess Revision: Acquiring the Rules of Chess Variants through FOL Theory Revision from Examples. ILP 2009: 123-130 - 2008
- [c5]Ana Luísa Duboc, Aline Paes, Gerson Zaverucha:
Using the Bottom Clause and Mode Declarations on FOL Theory Revision from Examples. ILP 2008: 91-106 - 2007
- [c4]Aline Paes, Gerson Zaverucha, Vítor Santos Costa:
Revising First-Order Logic Theories from Examples Through Stochastic Local Search. ILP 2007: 200-210 - 2006
- [c3]Aline Paes, Kate Revoredo, Gerson Zaverucha, Vítor Santos Costa:
PFORTE: Revising Probabilistic FOL Theories. IBERAMIA-SBIA 2006: 441-450 - [c2]Aline Paes, Filip Zelezný, Gerson Zaverucha, C. David Page Jr., Ashwin Srinivasan:
ILP Through Propositionalization and Stochastic k-Term DNF Learning. ILP 2006: 379-393 - 2005
- [c1]Aline Paes, Kate Revoredo, Gerson Zaverucha, Vítor Santos Costa:
Probabilistic First-Order Theory Revision from Examples. ILP 2005: 295-311
Coauthor Index
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