João Gama

João Gama, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

Learning about the Learning Process

João Gama, Petr Kosina, João Gama, 2011, IDA.

Contextual anomalies in medical data

João Gama, Pedro Pereira Rodrigues, Daniela Vasco, 2013, Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems.

Mobile Data Stream Mining: From Algorithms to Applications

Mohamed Medhat Gaber, Shonali Krishnaswamy, João Gama, 2012, 2012 IEEE 13th International Conference on Mobile Data Management.

Extração de conhecimento de dados: data mining

João Gama, Ana Carolina Lorena, André C. P. L. F. de Carvalho, 2015 .

Detection of Fraud Symptoms in the Retail Industry

Rita P. Ribeiro, João Gama, Ricardo Oliveira, 2016, IBERAMIA.

Resource Aware Distributed Knowledge Discovery

João Gama, Antoine Cornuéjols, João Gama, 2010, Ubiquitous Knowledge Discovery.

Proceedings of the 3rd Workshop on Ubiquitous Data Mining

João Gama, Michael May, Carlos Arthur Ferreira, 2013 .

Knowledge Discovery from Sensor Data

Mohamed Medhat Gaber, João Gama, Ranga Raju Vatsavai, 2008 .

Advances in data stream mining for mobile and ubiquitous environments

Mohamed Medhat Gaber, Shonali Krishnaswamy, João Gama, 2011, CIKM '11.

An Adaptive Predictive Model for Student Modeling

João Gama, Gladys Castillo, Ana Breda, 2006 .

Learning from medical data streams 2011: proceedings of the workshop on learning from medical data streams (LEMEDS'11), Bled, Slovenia, July 6, 2011.

Mykola Pechenizkiy, Mohamed Medhat Gaber, João Gama, 2011 .

Data Stream Mining: the Bounded Rationality

João Gama, João Gama, 2013, Informatica.

Requirements for Clustering Streaming Sensors

João Gama, Pedro Pereira Rodrigues, Luís M. B. Lopes, 2008 .

Linear tree

João Gama, Pavel Brazdil, 1999, Intell. Data Anal..

Accurate decision trees for mining high-speed data streams

João Gama, Pedro Medas, Ricardo Rocha, 2003, KDD '03.

Learning from Data Streams: Synopsis and Change Detection

João Gama, Teresa Mendonça, Raquel Sebastião, 2008, STAIRS.

Functional Trees

João Gama, João Gama, 2001, Machine Learning.

Trees, Probabilistic Functional†

João Gama, 2014 .

Processing Evolving Social Networks for Change Detection Based on Centrality Measures

João Gama, Fabiola S. F. Pereira, Sandra de Amo, 2018, Studies in Big Data.

Sequential Pattern Knowledge in Multi-Relational Learning

João Gama, Carlos Abreu Ferreira, Vítor Santos Costa, 2011, ISCIS.

Data Stream Classification Guided by Clustering on Nonstationary Environments and Extreme Verification Latency

João Gama, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, 2015, SDM.

Weightless neural networks for open set recognition

João Gama, Felipe Maia Galvão França, Douglas de O. Cardoso, 2017, Machine Learning.

Efficient Incremental Laplace Centrality Algorithm for Dynamic Networks

João Gama, Pavel Brazdil, Rui Portocarrero Sarmento, 2017, COMPLEX NETWORKS.

A Simple Dense Pixel Visualization for Mobile Sensor Data Mining

João Gama, Pedro Pereira Rodrigues, 2008, KDD Workshop on Knowledge Discovery from Sensor Data.

Ensembles of Classifiers

João Gama, O. Okun, 2011 .

Improving Mass Transit Operations by Using AVL-Based Systems: A Survey

João Gama, Luís Moreira-Matias, João Mendes-Moreira, 2015, IEEE Transactions on Intelligent Transportation Systems.

An Overview of Concept Drift Applications

Mykola Pechenizkiy, João Gama, Indrė Žliobaitė, 2016 .

Concept Drift in Decision Trees Learning from Data Streams

João Gama, Pedro Pereira Rodrigues, Pedro Medas, 2004 .

BRIGHT—Drift-Aware Demand Predictions for Taxi Networks

João Gama, Erik Jenelius, Luís Moreira-Matias, 2019, IEEE Transactions on Knowledge and Data Engineering.

Proceedings of the 3rd Workshop on Ubiquitous Data Mining co-located with the 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), Beijing, China, August 3, 2013

João Gama, Michael May, Faculdade de Economia, 2013, UDM@IJCAI.

Fading histograms in detecting distribution and concept changes

João Gama, Teresa Mendonça, Raquel Sebastião, 2017, International Journal of Data Science and Analytics.

Correcting Streaming Predictions of an Electricity Load Forecast System Using a Prediction Reliability Estimate

João Gama, Igor Kononenko, Pedro Pereira Rodrigues, 2011, ICMMI.

Online Semi-supervised Learning for Multi-target Regression in Data Streams Using AMRules

Ricardo Sousa, João Gama, João Gama, 2016, IDA.

Sequential anomalies: a study in the Railway Industry

Rita P. Ribeiro, João Gama, Pedro Mota Pereira, 2016, Machine Learning.

Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part II

João Gama, Annalisa Appice, Vítor Santos Costa, 2015, ECML/PKDD.

Where Are We Going? Predicting the Evolution of Individuals

Myra Spiliopoulou, João Gama, Márcia D. B. Oliveira, 2012, IDA.

Proceedings, Part II, of the European Conference on Machine Learning and Knowledge Discovery in Databases - Volume 9285

João Gama, Annalisa Appice, Carlos Soares, 2015 .

Functional Trees for Regression

João Gama, João Gama, 2001, IDA.

Assembled Feature Selection for Credit Scoring in Microfinance with Non-traditional Features

João Gama, Luís Rodrigues, Saulo Ruiz, 2020, DS.

Regression Trees from Data Streams with Drift Detection

João Gama, Dejan Gjorgjevikj, Raquel Sebastião, 2009, Discovery Science.

Analyzing the behavior dynamics of grain price indexes using Tucker tensor decomposition and spatio-temporal trajectories

João Gama, Pedro Luiz Pizzigatti Corrêa, Márcia D. B. Oliveira, 2016, Comput. Electron. Agric..

Visualization of evolving large scale ego-networks

João Gama, Rui Sarmento, Mário Cordeiro, 2015, SAC.

Proceedings of the Second international conference on Knowledge Discovery from Sensor Data

Nitesh V. Chawla, Mohamed Medhat Gaber, João Gama, 2008 .

Learning decision trees from dynamic data streams

João Gama, Pedro Pereira Rodrigues, Pedro Medas, 2005, SAC '05.

Challenges in Learning from Streaming Data Extended Abstract

João Gama, João Gama, 2014, ICT Innovations.

Proceedings of the Workshop on IoT Large Scale Learning from Data Streams co-located with the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), Skopje, Macedonia, September 18-22, 2017

Rita P. Ribeiro, João Gama, Mouchaweh, 2017, IOTSTREAMING@PKDD/ECML.

Incremental discretization, application to data with concept drift

João Gama, Carlos Pinto, 2007, SAC '07.

Clustering from Data Streams

João Gama, 2010, Encyclopedia of Machine Learning and Data Mining.

Hierarchical Time-Series Clustering for Data Streams ⋆

João Gama, João Pedro Pedroso, Pedro Pereira Rodrigues, 2004 .

Stream-Based Electricity Load Forecast

João Gama, Pedro Pereira Rodrigues, João Gama, 2007, PKDD.

Novelty detection in data streams

André Carlos Ponce de Leon Ferreira de Carvalho, Elaine Ribeiro de Faria, João Gama, 2015, Artificial Intelligence Review.

WCDS: A Two-Phase Weightless Neural System for Data Stream Clustering

João Gama, Felipe Maia Galvão França, Douglas de O. Cardoso, 2017, New Generation Computing.

Profiling high leverage points for detecting anomalous users in telecom data networks

João Gama, Muhammad Ajmal Azad, Shazia Tabassum, 2020, Annals of Telecommunications.

Cluster-based novel concept detection in data streams applied to intrusion detection in computer networks

André Carlos Ponce de Leon Ferreira de Carvalho, João Gama, Eduardo Jaques Spinosa, 2008, SAC '08.

Improving Portfolio Optimization Using Weighted Link Prediction in Dynamic Stock Networks

André Carlos Ponce de Leon Ferreira de Carvalho, João Gama, Douglas Castilho, 2019, ICCS.

Data stream clustering: A survey

André Carlos Ponce de Leon Ferreira de Carvalho, Elaine Ribeiro de Faria, João Gama, 2013, CSUR.

Spatiotemporal Traffic Anomaly Detection on Urban Road Network Using Tensor Decomposition Method

João Gama, Sofia da Silva Fernandes, Tonci Caric, 2020, DS.

Adapting ClusTree for more challenging data stream environments

João Gama, Andrzej Kasprzak, Jakub Zgraja, 2019, Journal of Intelligent & Fuzzy Systems.

Clustering of Time-Series Data Streams

João Gama, João Pedro Pedroso, Pedro Pereira Rodrigues, 2005 .

Learning from Data Streams

João Gama, Pedro Pereira Rodrigues, João Gama, 2009, Encyclopedia of Data Warehousing and Mining.

Collaborative filtering with recency-based negative feedback

João Gama, Alípio Mário Jorge, João Vinagre, 2015, SAC.

Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases

Luís Torgo, João Gama, Rui Camacho, 2005 .

Characterizing the Applicability of Classification Algorithms Using Meta-Level Learning

João Gama, Pavel Brazdil, Bob Henery, 1994, ECML.

Online Reliability Estimates for Individual Predictions in Data Streams

João Gama, Pedro Pereira Rodrigues, Zoran Bosnic, 2008, 2008 IEEE International Conference on Data Mining Workshops.

RUSE-WARMR: Rule Selection for Classifier Induction in Multi-relational Data-Sets

João Gama, Carlos Abreu Ferreira, Vítor Santos Costa, 2008, 2008 20th IEEE International Conference on Tools with Artificial Intelligence.

Evaluation Methodology for Multiclass Novelty Detection Algorithms

André Carlos Ponce de Leon Ferreira de Carvalho, Elaine Ribeiro de Faria, João Gama, 2013, 2013 Brazilian Conference on Intelligent Systems.

A local algorithm to approximate the global clustering of streams generated in ubiquitous sensor networks

João Gama, Pedro Pereira Rodrigues, Luís M. B. Lopes, 2018, Int. J. Distributed Sens. Networks.

Clustering from Data Streams

João Gama, João Gama, 2010, Encyclopedia of Machine Learning and Data Mining.

Machine Learning and Knowledge Discovery in Databases

João Gama, Annalisa Appice, Vítor Santos Costa, 2015, Lecture Notes in Computer Science.

An overview of social network analysis

João Gama, Márcia D. B. Oliveira, João Gama, 2012, WIREs Data Mining Knowl. Discov..

From mobility data to habits and common pathways

João Gama, Brais Cancela, Thiago Andrade, 2020, Expert Syst. J. Knowl. Eng..

Mobility Mining Using Nonnegative Tensor Factorization

Hadi Fanaee-T, João Gama, Hamid Eslami Nosratabadi, 2017, EPIA.

Dynamic Discretization of Continuous Attributes

Luís Torgo, João Gama, Carlos Soares, 1998, IBERAMIA.

Bipartite Graphs for Monitoring Clusters Transitions

João Gama, Márcia D. B. Oliveira, João Gama, 2010, IDA.

Discriminant Trees

João Gama, João Gama, 1999, ICML.

Incremental learning and concept drift: Editor's introduction

Paul E. Utgoff, João Gama, Miroslav Kubat, 2004, Intell. Data Anal..

IoT Big Data Stream Mining

Latifur Khan, Wei Fan, João Gama, 2016, KDD.

Comparing Data Distribution Using Fading Histograms

João Gama, Teresa Mendonça, Raquel Sebastião, 2014, ECAI.

On analyzing user preference dynamics with temporal social networks

João Gama, Gina Maira Barbosa de Oliveira, Fabiola S. F. Pereira, 2018, Machine Learning.

Avoiding Anomalies in Data Stream Learning

João Gama, Petr Kosina, Ezilda Almeida, 2013, Discovery Science.

Oblique Linear Tree

João Gama, João Gama, 1997, IDA.

Adaptation to Drifting Concepts

João Gama, Pedro Medas, Gladys Castillo, 2003, EPIA.

Evaluation of recommender systems in streaming environments pdf

João Gama, Alípio Mário Jorge, João Vinagre, 2015, ArXiv.

Tracking Recurring Concepts with Meta-learners

João Gama, Petr Kosina, João Gama, 2009, EPIA.

Keynote speakers

João Gama, 2016, 2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT).

Trustability in Algorithmic Systems Based on Artificial Intelligence in the Public and Private Sectors

João Gama, Pedro Amorim, Sónia Teixeira, 2020, ERCIM News.

Probabilistic Ramp Detection and Forecasting for Wind Power Prediction

João Gama, Carlos Abreu Ferreira, Vladimiro Miranda, 2013 .

Dynamic community detection in evolving networks using locality modularity optimization

João Gama, Rui Sarmento, Mário Cordeiro, 2016, Social Network Analysis and Mining.

Evolving Centralities in Temporal Graphs: A Twitter Network Analysis

João Gama, Fabiola S. F. Pereira, Sandra de Amo, 2016, 2016 17th IEEE International Conference on Mobile Data Management (MDM).

Eigenspace method for spatiotemporal hotspot detection pdf

Hadi Fanaee-T, João Gama, João Gama, 2014, Expert Syst. J. Knowl. Eng..

Predicting Ramp Events with a Stream-Based HMM Framework

João Gama, Carlos Abreu Ferreira, Vítor Santos Costa, 2012, Discovery Science.

Change Detection with Kalman Filter and CUSUM

João Gama, Milton Severo, João Gama, 2006, Discovery Science.

Time Series Data Streams

João Gama, 2010 .

Dynamic Laplace: Efficient Centrality Measure for Weighted or Unweighted Evolving Networks pdf

João Gama, Pavel Brazdil, Rui Portocarrero Sarmento, 2018, ArXiv.

Ubiquitous Data Mining

João Gama, João Gama, 2010 .

Discovering locations and habits from human mobility data

João Gama, Brais Cancela, Thiago Andrade, 2020, Annals of Telecommunications.

Visualization for Streaming Telecommunications Networks

João Gama, Rui Sarmento, Mário Cordeiro, 2014, NFMCP.

Proceedings of the 12th International Conference on Discovery Science

João Gama, Alípio Mário Jorge, Pavel Brazdil, 2009 .

Online bagging for recommender systems

João Gama, Alípio Mário Jorge, João Vinagre, 2018, Expert Syst. J. Knowl. Eng..

Recurrent concepts in data streams classification

João Gama, Petr Kosina, 2013, Knowledge and Information Systems.

Clustering in the Presence of Concept Drift

Herna L. Viktor, João Gama, Nathalie Japkowicz, 2018, ECML/PKDD.

Distributed clustering of ubiquitous data streams

João Gama, Pedro Pereira Rodrigues, João Gama, 2014, WIREs Data Mining Knowl. Discov..

Forgetting methods for incremental matrix factorization in recommender systems

Myra Spiliopoulou, João Gama, Alípio Mário Jorge, 2015, SAC.

Self Hyper-Parameter Tuning for Data Streams

João Gama, Benedita Malheiro, Bruno Veloso, 2018, DS.

Enhancing data stream predictions with reliability estimators and explanation

João Gama, Igor Kononenko, Pedro Pereira Rodrigues, 2014, Eng. Appl. Artif. Intell..

Sampling Evolving Ego-Networks with forgetting Factor

João Gama, Shazia Tabassum, 2016, 2016 17th IEEE International Conference on Mobile Data Management (MDM).

Personalised Dynamic Viewer Profiling for Streamed Data

João Gama, Juan C. Burguillo, Benedita Malheiro, 2018, WorldCIST.

Measures for Combining Prediction Intervals Uncertainty and Reliability in Forecasting

João Gama, Vânia Almeida, 2015, CORES.

An Analysis of Functional Trees

João Gama, João Gama, 2002, ICML.

Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data, Paris, France, June 28, 2009

Nitesh V. Chawla, Mohamed Medhat Gaber, João Gama, 2009, KDD Workshop on Knowledge Discovery from Sensor Data.

Proceedings of the Sixth International Workshop on Knowledge Discovery from Sensor Data

Nitesh V. Chawla, Mohamed Medhat Gaber, João Gama, 2009, KDD 2009.

Statistically Robust Evaluation of Stream-Based Recommender Systems

João Gama, Conceição Rocha, Alípio Mário Jorge, 2021, IEEE Transactions on Knowledge and Data Engineering.

L2GClust: local-to-global clustering of stream sources

João Gama, Pedro Pereira Rodrigues, Luís M. B. Lopes, 2011, SAC.

A survey on concept drift adaptation

João Gama, Abdelhamid Bouchachia, Albert Bifet, 2014, ACM Comput. Surv..

Ensemble learning for data stream analysis: A survey

João Gama, Bartosz Krawczyk, Leandro L. Minku, 2017, Inf. Fusion.

Advances in Intelligent Data Analysis X - 10th International Symposium, IDA 2011, Porto, Portugal, October 29-31, 2011. Proceedings

João Gama, Elizabeth Bradley, Jaakko Hollmén, 2011, IDA.

Recognizing Family, Genus, and Species of Anuran Using a Hierarchical Classification Approach

João Gama, Eduardo Freire Nakamura, Juan Gabriel Colonna, 2016, DS.

Selective sequencial integration on classification

João Gama, Carlos Ferreira, 2007 .

Visualizing the Evolution of Social Networks

João Gama, Márcia D. B. Oliveira, João Gama, 2011, EPIA.

Collaborative Wind Power Forecast

João Gama, Vânia Almeida, 2014, ICAIS.

MEC - Monitoring Clusters' Transitions

João Gama, Márcia D. B. Oliveira, 2010, STAIRS.

Tensor decomposition for analysing time-evolving social networks: an overview

Hadi Fanaee-T, João Gama, Sofia Fernandes, 2020, Artificial Intelligence Review.

On Using Temporal Networks to Analyze User Preferences Dynamics

João Gama, Fabiola S. F. Pereira, Sandra de Amo, 2016, DS.

Learning decision trees from dynamic data streams

João Gama, Pedro Medas, João Gama, 2005, SAC '05.

Proceedings of the sixth international workshop on knowledge discovery from sensor data (SensorKDD '12)

Nitesh V. Chawla, Mohamed Medhat Gaber, João Gama, 2012 .

Online tree-based ensembles and option trees for regression on evolving data streams

Saso Dzeroski, João Gama, Elena Ikonomovska, 2015, Neurocomputing.

Ensembles of Classifiers

João Gama, João Gama, 2010 .

Bike-Sharing Dataset

João Gama, T. Hadi Fanaee, João Gama, 2013 .

Weightless Neural Modeling for Mining Data Streams

João Gama, Felipe M. G. França, Douglas de O. Cardoso, 2018 .

Constructing fading histograms from data streams

João Gama, Teresa Mendonça, Raquel Sebastião, 2014, Progress in Artificial Intelligence.

Speeding-Up Hoeffding-Based Regression Trees With Options

Bernard Zenko, Saso Dzeroski, João Gama, 2011, ICML.

Iterative Naive Bayes

João Gama, 1999, Discovery Science.

Machine learning for streaming data: state of the art, challenges, and opportunities

João Gama, Heitor Murilo Gomes, Jesse Read, 2019, SKDD.

Time Series Data Streams

João Gama, João Gama, 2010 .

Combining classification algorithms

João Gama, João Gama, 2000 .

Data stream mining: from theory to applications and from stationary to mobile

Mohamed Medhat Gaber, Shonali Krishnaswamy, João Gama, 2010 .

Pursuing the Best ECOC Dimension for Multiclass Problems

André Carlos Ponce de Leon Ferreira de Carvalho, João Gama, Edgar Pimenta, 2007, FLAIRS Conference.

Decision trees for mining data streams

João Gama, Ricardo Fernandes, Ricardo Rocha, 2006, Intell. Data Anal..

Acute Kidney Injury Detection: An Alarm System to Improve Early Treatment

João Gama, Ana Rita Nogueira, Carlos Abreu Ferreira, 2017, ISMIS.

Progress in Artificial Intelligence: 18th EPIA Conference on Artificial Intelligence, EPIA 2017, Porto, Portugal, September 5-8, 2017, Proceedings

Zita Vale, João Gama, Henrique Lopes Cardoso, 2017, Lecture Notes in Computer Science.

ODAC: Hierarchical Clustering of Time Series Data Streams

João Gama, João Pedro Pedroso, Pedro Pereira Rodrigues, 2006, SDM.

Artificial Neural Networks Classification of Patients with Parkinsonism based on Gait

Estela Bicho, João Gama, Wolfram Erlhagen, 2018, 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

An Experimental Study on Predictive Models Using Hierarchical Time Series

Rita P. Ribeiro, João Gama, Ana M. Silva, 2015, EPIA.

First Principle Models Based Dataset Generation for Multi-Target Regression and Multi-Label Classification Evaluation

Ricardo Sousa, João Gama, João Gama, 2016, STREAMEVOLV@ECML-PKDD.

Certainty Equivalence Principle

Jean-Michel Renders, João Gama, Lise Getoor, 2010, Encyclopedia of Machine Learning and Data Mining.

Fast Incremental Matrix Factorization for Recommendation with Positive-Only Feedback

João Gama, Alípio Mário Jorge, João Vinagre, 2014, UMAP.

Adaptive Bayesian network classifiers

João Gama, Gladys Castillo, João Gama, 2009, Intell. Data Anal..

Clustering Techniques in Sensor Networks

João Gama, Pedro Pereira Rodrigues, João Gama, 2007 .

Click-Through Rate (CTR)

Jean-Michel Renders, João Gama, Eamonn J. Keogh, 2010, Encyclopedia of Machine Learning and Data Mining.

Research Challenges in Ubiquitous Knowledge Discovery

Koen Vanhoof, Katharina Morik, Donato Malerba, 2008, Next Generation of Data Mining.

Impact of Trust and Reputation Based Brokerage on the CloudAnchor Platform

João Gama, Juan C. Burguillo, Benedita Malheiro, 2020, PAAMS.

A Study on Imbalanced Data Streams

Rita P. Ribeiro, João Gama, Ehsan Aminian, 2019, PKDD/ECML Workshops.

Monitoring Incremental Histogram Distribution for Change Detection in Data Streams

João Gama, Pedro Pereira Rodrigues, João Bernardes, 2008, KDD Workshop on Knowledge Discovery from Sensor Data.

Constructive Induction on Continuous Spaces

João Gama, Pavel Brazdil, João Gama, 1998 .

The search of conditional outliers

Rita P. Ribeiro, João Gama, Eduarda Portela, 2019, Intell. Data Anal..

Random rules from data streams

João Gama, Petr Kosina, Ezilda Almeida, 2013, SAC '13.

Forgetting techniques for stream-based matrix factorization in recommender systems

Myra Spiliopoulou, João Gama, Alípio Mário Jorge, 2017, Knowledge and Information Systems.

Evaluating Streaming Algorithms

João Gama, 2010 .

Very Fast Decision Rules for multi-class problems

João Gama, Petr Kosina, 2012, SAC '12.

Multi-label classification from high-speed data streams with adaptive model rules and random rules

Ricardo Sousa, João Gama, 2018, Progress in Artificial Intelligence.

Knowledge Discovery from Sensor Data, Second International Workshop, Sensor-KDD 2008, Las Vegas, NV, USA, August 24-27, 2008, Revised Selected Papers

Nitesh V. Chawla, Mohamed Medhat Gaber, João Gama, 2010, KDD Workshop on Knowledge Discovery from Sensor Data.

Identifying Relationships in Transactional Data

João Gama, Carlos Abreu Ferreira, Melissa Rodrigues, 2012, IBERAMIA.

Learning from Data Streams: Processing Techniques in Sensor Networks

Mohamed Medhat Gaber, João Gama, João Gama, 2007 .

Issues in evaluation of stream learning algorithms

João Gama, Pedro Pereira Rodrigues, Raquel Sebastião, 2009, KDD.

Online Gradient Boosting for Incremental Recommender Systems

João Gama, Alípio Mário Jorge, João Vinagre, 2018, DS.

Estimating Reliability for Assessing and Correcting Individual Streaming Predictions

João Gama, Igor Kononenko, Pedro Pereira Rodrigues, 2012 .

Lecture Notes in Artificial Intelligence: Introduction

João Gama, Nuno C. Marques, Margarida G. M. S. Cardoso, 2005 .

Handling Time Changing Data with Adaptive Very Fast Decision Rules

João Gama, Petr Kosina, João Gama, 2012, ECML/PKDD.

Real-time algorithm for changes detection in depth of anesthesia signals

João Gama, Margarida Martins da Silva, Teresa Mendonça, 2013, Evol. Syst..

Ubiquitous Knowledge Discovery

João Gama, Michael May, 2011, IDA 2011.

Validating the coverage of bus schedules: A Machine Learning approach

João Gama, João Mendes-Moreira, Jorge Freire de Sousa, 2015, Inf. Sci..

OLINDDA: a cluster-based approach for detecting novelty and concept drift in data streams

André Carlos Ponce de Leon Ferreira de Carvalho, João Gama, Eduardo Jaques Spinosa, 2007, SAC '07.

Change Detection in Climate Data over the Iberian Peninsula

João Gama, Pedro Pereira Rodrigues, Raquel Sebastião, 2009, 2009 IEEE International Conference on Data Mining Workshops.

Co-training study for online regression

Ricardo Sousa, João Gama, 2018, SAC.

How to Correctly Evaluate an Automatic Bioacoustics Classification Method

João Gama, Eduardo Freire Nakamura, Juan Gabriel Colonna, 2016, CAEPIA.

Knowledge Discovery in Databases: PKDD 2005, 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, October 3-7, 2005, Proceedings

Luís Torgo, João Gama, Rui Camacho, 2005, PKDD.

Event and Anomaly Detection Using Tucker3 Decomposition pdf

Hadi Fanaee-T, João Gama, Simon Malinowski, 2014, ArXiv.

Best papers from the Fifth International Conference on Advanced Data Mining and Applications (ADMA 2009)

Jian Pei, Qiang Yang, João Gama, 2011, Knowledge and Information Systems.

The next generation of transportation systems,greenhouse emissions, and data mining

João Gama, Hillol Kargupta, Wei Fan, 2010, KDD.

Hierarchical Time Series Forecast in Electrical Grids

Rita P. Ribeiro, João Gama, Vania Gomes de Almeida, 2016 .

Novelty detection algorithm for data streams multi-class problems

André Carlos Ponce de Leon Ferreira de Carvalho, Elaine Ribeiro de Faria, João Gama, 2013, SAC '13.

Machine Learning: ECML 2005, 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings

Luís Torgo, João Gama, Rui Camacho, 2005, ECML.

Thesis: Inductive learning classification algorithms

João Gama, João Gama, 2000, AI Communications.

Unsupervised density-based behavior change detection in data streams

André Carlos Ponce de Leon Ferreira de Carvalho, João Gama, Rodrigo Fernandes de Mello, 2014, Intell. Data Anal..

Predictive Learning in Sensor Networks

Rasmus Ulslev Pedersen, João Gama, João Gama, 2007 .

Data stream mining in ubiquitous environments: state‐of‐the‐art and current directions

Mohamed Medhat Gaber, João Bártolo Gomes, Shonali Krishnaswamy, 2014, WIREs Data Mining Knowl. Discov..

A system for analysis and prediction of electricity-load streams

João Gama, Pedro Pereira Rodrigues, 2009, Intell. Data Anal..

Distributed Adaptive Model Rules for mining big data streams

João Gama, Gianmarco De Francisci Morales, Albert Bifet, 2014, 2014 IEEE International Conference on Big Data (Big Data).

Cover Image, Volume 8, Issue 5

João Gama, Fabíola S. F. Pereira, Fabiola S. F. Pereira, 2018, WIREs Data Mining Knowl. Discov..

Identifying, Ranking and Tracking Community Leaders in Evolving Social Networks

Masahiro Kimura, João Gama, Pavel Brazdil, 2019, COMPLEX NETWORKS.

A survey on learning from data streams: current and future trends

João Gama, João Gama, 2012, Progress in Artificial Intelligence.

Human Activity Recognition Using Inertial Sensors in a Smartphone: An Overview

João Gama, Khalil El-Khatib, Eduardo Souto, 2019, Sensors.

On Improving Operational Planning and Control in Public Transportation Networks using Streaming Data: A Machine Learning Approach

João Gama, João Mendes Moreira, Michel Ferreira, 2014 .

Learning model trees from evolving data streams

Saso Dzeroski, João Gama, Elena Ikonomovska, 2010, Data Mining and Knowledge Discovery.

Decision Trees Using the Minimum Entropy-of-Error Principle

Luís A. Alexandre, Joaquim Marques de Sá, João Gama, 2009, CAIP.

New Results on Minimum Error Entropy Decision Trees

Joaquim Marques de Sá, João Gama, Raquel Sebastião, 2011, CIARP.

Evaluation of Multiclass Novelty Detection Algorithms for Data Streams

André Carlos Ponce de Leon Ferreira de Carvalho, Elaine Ribeiro de Faria, João Gama, 2015, IEEE Transactions on Knowledge and Data Engineering.

Vehicular Sensing: Emergence of a Massive Urban Scanner

João Gama, Pedro M. d'Orey, Fernanda Lima, 2012, S-CUBE.

Contrasting logical sequences in multi-relational learning

João Gama, Carlos Abreu Ferreira, Vítor Santos Costa, 2019, Progress in Artificial Intelligence.

Physiological Data Modeling Contest

João Gama, Pedro Pereira Rodrigues, 2004 .

Speed and Size Characteristic of Concept Drift

João Gama, Raquel Sebastião, Petr Kosina, 2010 .

MINAS: multiclass learning algorithm for novelty detection in data streams

André Carlos Ponce de Leon Ferreira de Carvalho, Elaine Ribeiro de Faria, João Gama, 2016, Data Mining and Knowledge Discovery.

Identifying Points of Interest and Similar Individuals from Raw GPS Data pdf

João Gama, Thiago Andrade, 2019, ArXiv.

Proceedings of International Workshop on Knowledge Discovery from Ubiquitous Data Streams

João Gama, M. Gaber, J. Aguilar-Ruiz, 2007 .

Dynamic communities in evolving customer networks: an analysis using landmark and sliding windows

João Gama, Márcia D. B. Oliveira, Américo Guerreiro, 2014, Social Network Analysis and Mining.

Cascade Generalization

João Gama, Pavel Brazdil, João Gama, 2000, Machine Learning.

Data Stream Processing

João Gama, Pedro Pereira Rodrigues, João Gama, 2007 .

Improving the offline clustering stage of data stream algorithms in scenarios with variable number of clusters

André Carlos Ponce de Leon Ferreira de Carvalho, Elaine Ribeiro de Faria, João Gama, 2012, SAC '12.

Forest trees for on-line data

João Gama, Pedro Medas, Ricardo Rocha, 2004, SAC '04.

Clustering data streams using a forgetful neural model

João Gama, Felipe Maia Galvão França, Douglas de O. Cardoso, 2016, SAC.

Drift Severity Metric

João Gama, Raquel Sebastião, Petr Kosina, 2010, ECAI.

Proceedings of the 16th European conference on Machine Learning

Luís Torgo, João Gama, Rui Camacho, 2005 .

Electricity load forecast using data streams techniques

João Gama, Pedro Pereira Rodrigues, João Gama, 2007, Monde des Util. Anal. Données.

A predictive model for the passenger demand on a taxi network

João Gama, Michel Ferreira, Luís Moreira-Matias, 2012, 2012 15th International IEEE Conference on Intelligent Transportation Systems.

Iterative Bayes

João Gama, João Gama, 2000, Intell. Data Anal..

An evolutionary algorithm for clustering data streams with a variable number of clusters

João Gama, Eduardo R. Hruschka, Jonathan de Andrade Silva, 2017, Expert Syst. Appl..

Self Hyper-parameter Tuning for Stream Recommendation Algorithms

João Gama, Benedita Malheiro, Bruno Veloso, 2018, DMLE/IOTSTREAMING@PKDD/ECML.

Decision Trees from Data Streams

João Gama, João Gama, 2010 .

A Linear-Bayes Classifier

João Gama, 2000, IBERAMIA-SBIA.

UBIQUITOUS DATA MINING

João Gama, João Gama, 2018 .

A review on the combination of binary classifiers in multiclass problems

André Carlos Ponce de Leon Ferreira de Carvalho, João Gama, Ana Carolina Lorena, 2008, Artificial Intelligence Review.

Co-training Semi-supervised Learning for Single-Target Regression in Data Streams Using AMRules

Ricardo Sousa, João Gama, 2017, ISMIS.

Exploring multi-relational temporal databases with a propositional sequence miner

João Gama, Carlos Abreu Ferreira, Vítor Santos Costa, 2015, Progress in Artificial Intelligence.

Biased Dynamic Sampling for Temporal Network Streams

João Gama, Shazia Tabassum, 2018, COMPLEX NETWORKS.

A framework to monitor clusters evolution applied to economy and finance problems

João Gama, Márcia D. B. Oliveira, João Gama, 2012, Intell. Data Anal..

Event detection from traffic tensors: A hybrid model

João Gama, Hadi Fanaee-T, João Gama, 2016, Neurocomputing.

Learning Model Rules From High-Speed Data Streams

João Gama, Carlos Abreu Ferreira, Ezilda Almeida, 2013, UDM@IJCAI.

On fast and scalable recurring link’s prediction in evolving multi-graph streams

João Gama, Shazia Tabassum, Bruno Veloso, 2020, Network Science.

Guest editors introduction: special issue of the ECMLPKDD 2015 journal track

Concha Bielza, João Gama, Alípio Mário Jorge, 2015, Data Mining and Knowledge Discovery.

Trees, Probabilistic Functional

João Gama, 2005 .

Regression by Classification

Luís Torgo, João Gama, João Gama, 1996, SBIA.

Adaptive Model Rules from Data Streams

João Gama, Carlos Abreu Ferreira, Ezilda Almeida, 2013, ECML/PKDD.

Learning with Local Drift Detection

João Gama, Gladys Castillo, João Gama, 2006, ADMA.

Outliers and the Simpson's Paradox

Rita P. Ribeiro, João Gama, Eduarda Portela, 2017, MICAI.

Local Cascade Generalization

João Gama, João Gama, 1998, International Conference on Machine Learning.

Interconnect bypass fraud detection: a case study

João Gama, Shazia Tabassum, Bruno Veloso, 2020, Annals of Telecommunications.

Incremental multi-target model trees for data streams

Saso Dzeroski, João Gama, Elena Ikonomovska, 2011, SAC.

User Preference Dynamics on Evolving Social Networks - Learning, Modeling and Prediction

João Gama, Fabiola S. F. Pereira, Gina M. B. Oliveira, 2019, Anais Estendidos do Simpósio Brasileiro de Sistemas Multimídia e Web (WebMedia).

Guest Editors introduction: special issue of the ECMLPKDD 2015 journal track

Concha Bielza, João Gama, Alípio Mário Jorge, 2015, Machine Learning.

Combining Classifiers by Constructive Induction

João Gama, João Gama, 1998, ECML.

A comparison of hierarchical multi-output recognition approaches for anuran classification

João Gama, Eduardo Freire Nakamura, Juan Gabriel Colonna, 2018, Machine Learning.

Multi-aspect renewable energy forecasting

Michelangelo Ceci, Hadi Fanaee-T, João Gama, 2021, Inf. Sci..

Automatic Classification of Anuran Sounds Using Convolutional Neural Networks

João Gama, Carlos Abreu Ferreira, Alípio Mário Jorge, 2016, C3S2E.

On Data and Algorithms: Understanding Inductive Performance

João Gama, Melanie Hilario, Alexandros Kalousis, 2004, Machine Learning.

An Overview on Mining Data Streams

João Gama, Pedro Pereira Rodrigues, João Gama, 2009, Foundations of Computational Intelligence.

Contributions to a decision support system based on depth of anesthesia signals

João Gama, Margarida Martins da Silva, Teresa Mendonça, 2012, 2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS).

Robust Division in Clustering of Streaming Time Series

João Gama, Pedro Pereira Rodrigues, 2008, ECAI.

Learning Model Trees from Data Streams

João Gama, Elena Ikonomovska, 2008, Discovery Science.

A Density-Based Clustering Approach for Behavior Change Detection in Data Streams

André Carlos Ponce de Leon Ferreira de Carvalho, João Gama, Jose Augusto Andrade Filho, 2012, 2012 Brazilian Symposium on Neural Networks.

Next challenges for adaptive learning systems

Katarzyna Musial, Mohamed Medhat Gaber, João Gama, 2012, SKDD.

Detecting Bursts of Activity in Telecommunications

João Gama, Bruno Veloso, Carlos Martins, 2019, BigMine@KDD.

A Weightless Neural Network-Based Approach for Stream Data Clustering

João Gama, Massimo De Gregorio, Felipe Maia Galvão França, 2012, IDEAL.

Evaluating Streaming Algorithms

João Gama, João Gama, 2010 .

Introduction to the Knowledge Discovery from Sensor Data

Nitesh V. Chawla, Mohamed Medhat Gaber, João Gama, 2008 .

Clustering data streams with weightless neural networks

João Gama, Massimo De Gregorio, Felipe Maia Galvão França, 2011, ESANN.

Proceedings of the Fourth International Workshop on Knowledge Discovery from Sensor Data (SensorKDD’10)

Nitesh V. Chawla, Mohamed Medhat Gaber, João Gama, 2010 .

A bounded neural network for open set recognition

João Gama, Felipe Maia Galvão França, Douglas de O. Cardoso, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Database Systems for Advanced Applications

Jun Yang, João Gama, Yongxin Tong, 2019, Lecture Notes in Computer Science.

Adaptive Bayes for a Student Modeling Prediction Task Based on Learning Styles

João Gama, Gladys Castillo, Ana M. Breda, 2003, User Modeling.

Online Social Networks Event Detection: A Survey

João Gama, Mário Cordeiro, João Gama, 2016, Solving Large Scale Learning Tasks.

Classification and Recommendation With Data Streams

João Gama, Bruno Veloso, Benedita Malheiro, 2021 .

A Framework for Analysing Dynamic Communities in Large-scale Social Networks

João Gama, Márcia D. B. Oliveira, Vítor Cerqueira, 2015, ICEIS.

Semi-fuzzy Splitting in Online Divisive-Agglomerative Clustering

João Gama, Pedro Pereira Rodrigues, João Gama, 2007, EPIA Workshops.

An overview on the exploitation of time in collaborative filtering

João Gama, Alípio Mário Jorge, João Vinagre, 2015, WIREs Data Mining Knowl. Discov..

Data Stream Mining Algorithms for Building Decision Models in a Computer Role-Playing Game Simulation

André Carlos Ponce de Leon Ferreira de Carvalho, João Gama, Rosane Maria Maffei Vallim, 2010, 2010 Brazilian Symposium on Games and Digital Entertainment.

Predictive Sequence Miner in ILP Learning

João Gama, Carlos Abreu Ferreira, Vítor Santos Costa, 2011, ILP.

Computational Models for Social and Technical Interactions

João Gama, Eugénio C. Oliveira, Henrique Lopes Cardoso, 2017, New Generation Computing.

Learning Decision Rules from Data Streams

João Gama, Petr Kosina, 2011, IJCAI.

Evolving Social Networks Analysis via Tensor Decompositions: From Global Event Detection Towards Local Pattern Discovery and Specification

Hadi Fanaee-T, João Gama, Sofia da Silva Fernandes, 2019, DS.

Reasoning about the Learning Process

João Gama, 2011, EGC.

Streaming Networks Sampling using top-K Networks

João Gama, Rui Sarmento, Mário Cordeiro, 2015, ICEIS.

The Application of Hierarchical Clustering Algorithms for Recognition Using Biometrics of the Hand

João Gama, Lúcia Sousa, João Gama, 2014 .

Feature ranking in hoeffding algorithms for regression

João Gama, João Duarte, João Gama, 2017, SAC.

Knowledge discovery from data streams

Mohamed Medhat Gaber, João Gama, Olufemi A. Omitaomu, 2009, IDA 2009.

A new dynamic modeling framework for credit risk assessment

João Gama, Elísio Brandão, Maria Rocha Sousa, 2016, Expert Syst. Appl..

Evolving Networks and Social Network Analysis Methods and Techniques

João Gama, Pavel Brazdil, Rui Portocarrero Sarmento, 2018, Social Media and Journalism - Trends, Connections, Implications.

Proceedings of the 3rd International Conference on Ubiquitous Data Mining - Volume 1088

Paulo Cortez, João Gama, Nuno C. Marques, 2013 .

Advances in Intelligent Data Analysis - Proceedings of the 10th International Symposium (IDA 2011)

João Gama, Jaakko Hollmén, Elizabeth Bradley, 2011 .

Clustering distributed sensor data streams using local processing and reduced communication

João Gama, Pedro Pereira Rodrigues, Luís M. B. Lopes, 2011, Intell. Data Anal..

Credit Scoring in Microfinance Using Non-traditional Data

João Gama, Saulo Ruiz, Pedro Gomes, 2017, EPIA.

NORMO: A new method for estimating the number of components in CP tensor decomposition

Hadi Fanaee-T, João Gama, Sofia Fernandes, 2020, Eng. Appl. Artif. Intell..

Sequential Pattern Mining in Multi-relational Datasets

João Gama, Carlos Abreu Ferreira, Vítor Santos Costa, 2009, CAEPIA.

Clustering Distributed Sensor Data Streams

João Gama, Pedro Pereira Rodrigues, Luís M. B. Lopes, 2008, ECML/PKDD.

Improving Incremental Recommenders with Online Bagging

João Gama, Alípio Mário Jorge, João Vinagre, 2017, EPIA.

Online Bagging for Recommendation with Incremental Matrix Factorization pdf

João Gama, Alípio Mário Jorge, João Vinagre, 2016, STREAMEVOLV@ECML-PKDD.

Bias Management of Bayesian Network Classifiers

João Gama, Gladys Castillo, 2005, Discovery Science.

Adaptive Model Rules From High-Speed Data Streams

João Gama, João Duarte, João Gama, 2014, BigMine.

Scalable Online Top-N Recommender Systems

Myra Spiliopoulou, João Gama, Marcos Aurélio Domingues, 2016, EC-Web.

Learning with Drift Detection

João Gama, Pedro Pereira Rodrigues, Pedro Medas, 2004, SBIA.

Hierarchical Clustering of Time-Series Data Streams

João Gama, João Pedro Pedroso, Pedro Pereira Rodrigues, 2008, IEEE Transactions on Knowledge and Data Engineering.

WINTENDED: WINdowed TENsor decomposition for Densification Event Detection in time-evolving networks

Hadi Fanaee-T, João Gama, Tomislav Šmuc, 2021, Machine Learning.

Forecasting conditional extreme quantiles for wind energy

João Gama, Ricardo J. Bessa, Laura Cavalcante, 2021 .

Generalised Partial Association in Causal Rules Discovery

João Gama, Carlos Abreu Ferreira, Ana Rita Nogueira, 2021, EPIA.

Text documents streams with improved incremental similarity

João Gama, Pavel Brazdil, Rui Portocarrero Sarmento, 2021, Social Network Analysis and Mining.

Modelling Voting Behaviour During a General Election Campaign Using Dynamic Bayesian Networks

João Gama, Ana Rita Nogueira, Patrício Costa, 2021, EPIA.

Using network features for credit scoring in microfinance

João Gama, Saulo Ruiz, Pedro Gomes, 2021, Int. J. Data Sci. Anal..

Dynamic Topic Modeling Using Social Network Analytics

João Gama, Shazia Tabassum, Paulo Azevedo, 2021, EPIA.

A Study on Change Detection Methods

João Gama, Raquel Sebastião, João Gama, 2009 .

Semi-supervised learning : predicting activities in Android environment

João Gama, João Mendes-Moreira, João Gama, 2013 .

Gait stride-to-stride variability and foot clearance pattern analysis in Idiopathic Parkinson's Disease and Vascular Parkinsonism.

Estela Bicho, João Gama, Nuno Sousa, 2019, Journal of biomechanics.

Exploiting Parallelism in Decision Tree Induction

João Gama, Fernando Silva, Nuno Amado, 2007 .

Análise exploratória de hierarquias em base de dados multidimensionais

João Gama, Nuno G.C. Ferreira, 2012 .

Holistic distributed stream clustering for smart grids

João Gama, Pedro Pereira Rodrigues, João Gama, 2013 .

New Concepts in Wind Power Forecasting Models

João Gama, Vladimiro Miranda, Audun Botterud, 2008 .

Introducing time-changing economics into credit scoring

João Gama, Elísio Brandão, Maria Rocha Sousa, 2013 .

Issues and Challenges in Learning from Data Streams Extended Abstract

João Gama, João Gama, 2007 .