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ORCIDJoão Gama 0001
João Manuel Portela da Gama
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- affiliation: University of Porto, Laboratory of Artificial Intelligence and Decision Support (LIAAD), Portugal
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2020 – today
- 2022
[j124]João Gama, Rita P. Ribeiro
, Bruno Veloso:
Data-Driven Predictive Maintenance. IEEE Intell. Syst. 37(4): 27-29 (2022)- [j123]Inês Martins, João S. Resende, Patrícia R. Sousa, Simão Silva, Luis Antunes, João Gama:
Host-based IDS: A review and open issues of an anomaly detection system in IoT. Future Gener. Comput. Syst. 133: 95-113 (2022) - [j122]Ana Rita Nogueira, Carlos Abreu Ferreira, João Gama:
Semi-causal decision trees. Prog. Artif. Intell. 11(1): 105-119 (2022) - [j121]Ana Rita Nogueira, Andrea Pugnana, Salvatore Ruggieri, Dino Pedreschi, João Gama:
Methods and tools for causal discovery and causal inference. WIREs Data Mining Knowl. Discov. 12(2) (2022) - [c206]Ana Rita Nogueira, Carlos Abreu Ferreira, João Gama:
Temporal Nodes Causal Discovery for in Intensive Care Unit Survival Analysis. EPIA 2022: 587-598 - [c205]Thiago Andrade, João Gama:
How are you Riding? Transportation Mode Identification from Raw GPS Data. EPIA 2022: 648-659 - [c204]Sónia Teixeira, José Rodrigues, Bruno Veloso, João Gama:
An Exploratory Diagnosis of Artificial Intelligence Risks for a Responsible Governance. ICEGOV 2022: 25-31 - [c203]Narjes Davari, Sepideh Pashami, Bruno Veloso, Slawomir Nowaczyk, Yuantao Fan, Pedro Mota Pereira, Rita P. Ribeiro, João Gama:
A Fault Detection Framework Based on LSTM Autoencoder: A Case Study for Volvo Bus Data Set. IDA 2022: 39-52 - [c202]Nirbhaya Shaji, João Gama, Rita P. Ribeiro, Pedro Gomes:
Bank Statements to Network Features: Extracting Features Out of Time Series Using Visibility Graph. IDA 2022: 278-289 - [e29]João Gama, Tianrui Li, Yang Yu, Enhong Chen, Yu Zheng, Fei Teng:
Advances in Knowledge Discovery and Data Mining - 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, May 16-19, 2022, Proceedings, Part I. Lecture Notes in Computer Science 13280, Springer 2022, ISBN 978-3-031-05932-2 [contents] - [e28]João Gama, Tianrui Li, Yang Yu, Enhong Chen, Yu Zheng, Fei Teng:
Advances in Knowledge Discovery and Data Mining - 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, May 16-19, 2022, Proceedings, Part II. Lecture Notes in Computer Science 13281, Springer 2022, ISBN 978-3-031-05935-3 [contents] - [e27]João Gama, Tianrui Li, Yang Yu, Enhong Chen, Yu Zheng, Fei Teng:
Advances in Knowledge Discovery and Data Mining - 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, May 16-19, 2022, Proceedings, Part III. Lecture Notes in Computer Science 13282, Springer 2022, ISBN 978-3-031-05980-3 [contents] - [i23]Alexis Bondu, Youssef Achenchabe, Albert Bifet, Fabrice Clérot, Antoine Cornuéjols, João Gama, Georges Hébrail, Vincent Lemaire, Pierre-François Marteau:
Open challenges for Machine Learning based Early Decision-Making research. CoRR abs/2204.13111 (2022) - [i22]Paula Raissa Silva, João Viangre, João Gama:
Federated Anomaly Detection over Distributed Data Streams. CoRR abs/2205.07829 (2022) - [i21]Rui Portocarrero Sarmento, Douglas de O. Cardoso, João Gama, Pavel Brazdil:
Contextualization for the Organization of Text Documents Streams. CoRR abs/2206.02632 (2022) - [i20]Bruno Veloso, João Gama, Rita P. Ribeiro, Pedro Mota Pereira:
A Benchmark dataset for predictive maintenance. CoRR abs/2207.05466 (2022) - [i19]Sérgio M. Jesus, José Pombal, Duarte Alves, André Ferreira Cruz, Pedro Saleiro, Rita P. Ribeiro, João Gama, Pedro Bizarro:
Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation. CoRR abs/2211.13358 (2022) - [i18]Sónia Teixeira, José Rodrigues, Bruno Veloso, João Gama:
Humans Versus Machines: The Perspective of Two Different Approaches in Classification for Ethical Design. ERCIM News 2022(131) (2022) - 2021
- [j120]Sofia Fernandes, Hadi Fanaee-T, João Gama:
Tensor decomposition for analysing time-evolving social networks: an overview. Artif. Intell. Rev. 54(4): 2891-2916 (2021) - [j119]Adrien Bécue, Isabel Praça, João Gama:
Artificial intelligence, cyber-threats and Industry 4.0: challenges and opportunities. Artif. Intell. Rev. 54(5): 3849-3886 (2021) - [j118]Ehsan Aminian, Rita P. Ribeiro, João Gama:
Chebyshev approaches for imbalanced data streams regression models. Data Min. Knowl. Discov. 35(6): 2389-2466 (2021) - [j117]Paulo Paraíso, Saulo Ruiz, Pedro Gomes, Luís Rodrigues, João Gama:
Using network features for credit scoring in microfinance. Int. J. Data Sci. Anal. 12(2): 121-134 (2021) - [j116]Bruno Veloso, João Gama, Benedita Malheiro, João Vinagre:
Hyperparameter self-tuning for data streams. Inf. Fusion 76: 75-86 (2021) - [j115]Roberto Corizzo, Michelangelo Ceci, Hadi Fanaee-T, João Gama:
Multi-aspect renewable energy forecasting. Inf. Sci. 546: 701-722 (2021) - [j114]Narjes Davari, Bruno Veloso, Gustavo de Assis Costa, Pedro Mota Pereira, Rita P. Ribeiro, João Gama:
A Survey on Data-Driven Predictive Maintenance for the Railway Industry. Sensors 21(17): 5739 (2021) - [j113]Rui Portocarrero Sarmento, Douglas de O. Cardoso, Kemmily Dearo, Pavel Brazdil, João Gama:
Text documents streams with improved incremental similarity. Soc. Netw. Anal. Min. 11(1): 113 (2021) - [j112]João Vinagre, Alípio Mário Jorge, Conceição Rocha, João Gama:
Statistically Robust Evaluation of Stream-Based Recommender Systems. IEEE Trans. Knowl. Data Eng. 33(7): 2971-2982 (2021) - [j111]Maroua Bahri, Albert Bifet, João Gama, Heitor Murilo Gomes, Silviu Maniu:
Data stream analysis: Foundations, major tasks and tools. WIREs Data Mining Knowl. Discov. 11(3) (2021) - [c201]João Gama, Bruno Veloso, Ehsan Aminian, Rita P. Ribeiro:
Current Trends in Learning from Data Streams. BDA 2021: 183-193 - [c200]Jean-Gabriel Gaudreault, Paula Branco, João Gama:
An Analysis of Performance Metrics for Imbalanced Classification. DS 2021: 67-77 - [c199]Narjes Davari, Bruno Veloso, Rita P. Ribeiro, Pedro Mota Pereira, João Gama:
Predictive maintenance based on anomaly detection using deep learning for air production unit in the railway industry. DSAA 2021: 1-10 - [c198]Ana Rita Nogueira, Carlos Abreu Ferreira, João Gama, Alberto A. Pinto:
Generalised Partial Association in Causal Rules Discovery. EPIA 2021: 485-497 - [c197]Shazia Tabassum, João Gama, Paulo Azevedo, Luis Teixeira, Carlos Martins, Andre Martins:
Dynamic Topic Modeling Using Social Network Analytics. EPIA 2021: 498-509 - [c196]Patrício Costa, Ana Rita Nogueira, João Gama:
Modelling Voting Behaviour During a General Election Campaign Using Dynamic Bayesian Networks. EPIA 2021: 524-536 - [c195]Sérgio M. Jesus, Catarina Belém, Vladimir Balayan, João Bento, Pedro Saleiro, Pedro Bizarro, João Gama:
How can I choose an explainer?: An Application-grounded Evaluation of Post-hoc Explanations. FAccT 2021: 805-815 - [c194]Bruno Veloso, Luciano Caroprese, Matthias König, Sónia Teixeira, Giuseppe Manco, Holger H. Hoos, João Gama:
Hyper-parameter Optimization for Latent Spaces. ECML/PKDD (3) 2021: 249-264 - [c193]Sónia Teixeira, Guilherme Londres, Bruno Veloso, Rita P. Ribeiro, João Gama:
Improving Smart Waste Collection Using AutoML. PKDD/ECML Workshops (2) 2021: 283-298 - [c192]Ricardo Cerri, Joel David Costa Jínior, Elaine R. Faria, João Gama:
A new self-organizing map based algorithm for multi-label stream classification. SAC 2021: 418-426 - [e26]Pedro Henriques Abreu, Pedro Pereira Rodrigues, Alberto Fernández, João Gama:
Advances in Intelligent Data Analysis XIX - 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26-28, 2021, Proceedings. Lecture Notes in Computer Science 12695, Springer 2021, ISBN 978-3-030-74250-8 [contents] - [e25]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee A. D. Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I. Communications in Computer and Information Science 1524, Springer 2021, ISBN 978-3-030-93735-5 [contents] - [e24]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee A. D. Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II. Communications in Computer and Information Science 1525, Springer 2021, ISBN 978-3-030-93732-4 [contents] - [i17]Sérgio M. Jesus, Catarina Belém, Vladimir Balayan, João Bento, Pedro Saleiro, Pedro Bizarro, João Gama:
How can I choose an explainer? An Application-grounded Evaluation of Post-hoc Explanations. CoRR abs/2101.08758 (2021) - [i16]Douglas Castilho, Tharsis T. P. Souza, Soong Moon Kang, João Gama, André C. P. L. F. de Carvalho:
Forecasting Financial Market Structure from Network Features using Machine Learning. CoRR abs/2110.11751 (2021) - 2020
- [j110]Albert Bifet, João Gama:
IoT data stream analytics. Ann. des Télécommunications 75(9-10): 491-492 (2020) - [j109]Thiago Andrade, Brais Cancela, João Gama:
Discovering locations and habits from human mobility data. Ann. des Télécommunications 75(9-10): 505-521 (2020) - [j108]Shazia Tabassum, Muhammad Ajmal Azad, João Gama:
Profiling high leverage points for detecting anomalous users in telecom data networks. Ann. des Télécommunications 75(9-10): 573-581 (2020) - [j107]Bruno Veloso, Shazia Tabassum, Carlos Martins, Raphael Espanha, Raul Azevedo, João Gama:
Interconnect bypass fraud detection: a case study. Ann. des Télécommunications 75(9-10): 583-596 (2020) - [j106]Felipe Azevedo Pinage, Eulanda Miranda dos Santos, João Gama:
A drift detection method based on dynamic classifier selection. Data Min. Knowl. Discov. 34(1): 50-74 (2020) - [j105]Sofia Fernandes, Hadi Fanaee-T, João Gama:
NORMO: A new method for estimating the number of components in CP tensor decomposition. Eng. Appl. Artif. Intell. 96: 103926 (2020) - [j104]Thiago Andrade, Brais Cancela, João Gama:
From mobility data to habits and common pathways. Expert Syst. J. Knowl. Eng. 37(6) (2020) - [j103]Brais Cancela, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, João Gama:
A scalable saliency-based feature selection method with instance-level information. Knowl. Based Syst. 192: 105326 (2020) - [j102]Shazia Tabassum, Bruno Veloso, João Gama:
On fast and scalable recurring link's prediction in evolving multi-graph streams. Netw. Sci. 8(S1): S65-S81 (2020) - [j101]Amal Saadallah, Luís Moreira-Matias, Ricardo Sousa, Jihed Khiari, Erik Jenelius, João Gama:
BRIGHT - Drift-Aware Demand Predictions for Taxi Networks. IEEE Trans. Knowl. Data Eng. 32(2): 234-245 (2020) - [c191]Maroua Bahri, Bruno Veloso, Albert Bifet, João Gama:
AutoML for Stream k-Nearest Neighbors Classification. IEEE BigData 2020: 597-602 - [c190]Teru Fujii, Masahito Kumano, João Gama, Masahiro Kimura:
Detecting Geographical Competitive Structure for POI Visit Dynamics. COMPLEX NETWORKS (2) 2020: 27-38 - [c189]Saulo Ruiz, Pedro Gomes, Luís Rodrigues, João Gama:
Assembled Feature Selection for Credit Scoring in Microfinance with Non-traditional Features. DS 2020: 207-216 - [c188]Leo Tisljaric, Sofia Fernandes, Tonci Caric, João Gama:
Spatiotemporal Traffic Anomaly Detection on Urban Road Network Using Tensor Decomposition Method. DS 2020: 674-688 - [c187]Paulo Paraíso, Pedro Gomes, Saulo Ruiz, Luís Rodrigues, João Gama:
Using Network Features for Credit Scoring in MicroFinance: Extended Abstract. DSAA 2020: 783-784 - [c186]Ana Rita Nogueira, João Gama, Carlos Abreu Ferreira:
Improving Prediction with Causal Probabilistic Variables. IDA 2020: 379-390 - [c185]Bruno Veloso, Benedita Malheiro, Juan-Carlos Burguillo, João Gama:
Impact of Trust and Reputation Based Brokerage on the CloudAnchor Platform. PAAMS 2020: 303-314 - [c184]Bruno Veloso, João Gama:
Self Hyper-parameter Tuning for Stream Classification Algorithms. IoT Streams/ITEM@PKDD/ECML 2020: 3-13 - [c183]Mariana Barros, Bruno Veloso, Pedro Mota Pereira, Rita P. Ribeiro, João Gama:
Failure Detection of an Air Production Unit in Operational Context. IoT Streams/ITEM@PKDD/ECML 2020: 61-74 - [c182]Bruno Veloso, Carlos Martins, Raphael Espanha, Raul Azevedo, João Gama:
Fraud detection using heavy hitters: a case study. SAC 2020: 482-489 - [e23]Albert Bifet, Michele Berlingerio, João Gama, Jesse Read, Ana Rita Nogueira:
Proceedings of the 8th International Workshop on Big Data, IoT Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications co-located with 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), Anchorage, Alaska, August 4-8, 2019. CEUR Workshop Proceedings 2579, CEUR-WS.org 2020 [contents] - [e22]Irena Koprinska, Michael Kamp, Annalisa Appice, Corrado Loglisci, Luiza Antonie, Albrecht Zimmermann, Riccardo Guidotti, Özlem Özgöbek, Rita P. Ribeiro, Ricard Gavaldà, João Gama, Linara Adilova, Yamuna Krishnamurthy, Pedro M. Ferreira, Donato Malerba, Ibéria Medeiros, Michelangelo Ceci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras, Peter Christen, Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Anna Monreale, Przemyslaw Biecek, Salvatore Rinzivillo, Benjamin Kille, Andreas Lommatzsch, Jon Atle Gulla:
ECML PKDD 2020 Workshops - Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020, Ghent, Belgium, September 14-18, 2020, Proceedings. Communications in Computer and Information Science 1323, Springer 2020, ISBN 978-3-030-65964-6 [contents] - [e21]João Gama, Sepideh Pashami, Albert Bifet, Moamar Sayed Mouchaweh, Holger Fröning, Franz Pernkopf, Gregor Schiele, Michaela Blott:
IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning - Second International Workshop, IoT Streams 2020, and First International Workshop, ITEM 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14-18, 2020, Revised Selected Papers. Communications in Computer and Information Science 1325, Springer 2020, ISBN 978-3-030-66769-6 [contents] - [i15]Jie Lu, Anjin Liu, Fan Dong, Feng Gu, João Gama, Guangquan Zhang:
Learning under Concept Drift: A Review. CoRR abs/2004.05785 (2020) - [i14]Ricardo Cerri, Joel David Costa Júnior, Elaine Ribeiro de Faria Paiva, João Manuel Portela da Gama:
Multi-label Stream Classification with Self-Organizing Maps. CoRR abs/2004.09397 (2020) - [i13]Sónia Teixeira, João Gama, Pedro Amorim, Gonçalo Figueira:
Trustability in Algorithmic Systems Based on Artificial Intelligence in the Public and Private Sectors. ERCIM News 2020(122) (2020)
2010 – 2019
- 2019
- [j100]Guoliang Li, João Gama, Jun Yang:
Special Issue of DASFAA 2019. Data Sci. Eng. 4(3): 177-178 (2019) - [j99]Eduarda Portela, Rita P. Ribeiro, João Gama:
The search of conditional outliers. Intell. Data Anal. 23(1): 23-39 (2019) - [j98]Saulo Ruiz, Pedro Gomes, Luís Rodrigues, João Gama:
Credit scoring for microfinance using behavioral data in emerging markets. Intell. Data Anal. 23(6): 1355-1378 (2019) - [j97]Jakub Zgraja, Richard Hugh Moulton, João Gama, Andrzej Kasprzak, Michal Wozniak:
Adapting ClusTree for more challenging data stream environments. J. Intell. Fuzzy Syst. 37(6): 7679-7688 (2019) - [j96]Carlos Abreu Ferreira, João Gama, Vítor Santos Costa:
Contrasting logical sequences in multi-relational learning. Prog. Artif. Intell. 8(4): 487-503 (2019) - [j95]Wesllen Sousa Lima, Eduardo Souto, Khalil El-Khatib, Roozbeh Jalali, João Gama:
Human Activity Recognition Using Inertial Sensors in a Smartphone: An Overview. Sensors 19(14): 3213 (2019) - [j94]Heitor Murilo Gomes, Jesse Read, Albert Bifet, Jean Paul Barddal, João Gama:
Machine learning for streaming data: state of the art, challenges, and opportunities. SIGKDD Explor. 21(2): 6-22 (2019) - [j93]Jie Lu, Anjin Liu, Fan Dong, Feng Gu, João Gama, Guangquan Zhang:
Learning under Concept Drift: A Review. IEEE Trans. Knowl. Data Eng. 31(12): 2346-2363 (2019) - [c181]Joel D. Costa Júnior, Elaine Ribeiro de Faria, Jonathan de Andrade Silva, João Gama, Ricardo Cerri:
Novelty Detection for Multi-Label Stream Classification. BRACIS 2019: 144-149 - [c180]Mário Cordeiro, Rui Portocarrero Sarmento, Pavel Brazdil, Masahiro Kimura, João Gama:
Identifying, Ranking and Tracking Community Leaders in Evolving Social Networks. COMPLEX NETWORKS (1) 2019: 198-210 - [c179]Andreia Conceição, João Gama:
Main Factors Driving the Open Rate of Email Marketing Campaigns. DS 2019: 145-154 - [c178]Sofia Fernandes, Hadi Fanaee-T, João Gama:
Evolving Social Networks Analysis via Tensor Decompositions: From Global Event Detection Towards Local Pattern Discovery and Specification. DS 2019: 385-395 - [c177]Thiago Andrade, Brais Cancela, João Gama:
Discovering Common Pathways Across Users' Habits in Mobility Data. EPIA (2) 2019: 410-421 - [c176]Douglas Castilho, João Gama, Leandro Resende Mundim, André C. P. L. F. de Carvalho:
Improving Portfolio Optimization Using Weighted Link Prediction in Dynamic Stock Networks. ICCS (3) 2019: 340-353 - [c175]Amal Saadallah, Luís Moreira-Matias, Ricardo Sousa, Jihed Khiari, Erik Jenelius, João Gama:
BRIGHT - Drift-Aware Demand Predictions for Taxi Networks (Extended Abstract). ICDE 2019: 2145-2146 - [c174]Joel D. Costa Júnior, Elaine R. Faria, Jonathan de Andrade Silva, João Gama, Ricardo Cerri:
Pruned Sets for Multi-Label Stream Classification without True Labels. IJCNN 2019: 1-8 - [c173]Bruno Veloso, Carlos Martins, Raphael Espanha, Raul Azevedo, João Gama:
Detecting Bursts of Activity in Telecommunications. BigMine@KDD 2019 - [c172]Ehsan Aminian, Rita P. Ribeiro, João Gama:
A Study on Imbalanced Data Streams. PKDD/ECML Workshops (2) 2019: 380-389 - [c171]Thiago Andrade, Brais Cancela, João Gama:
Mining Human Mobility Data to Discover Locations and Habits. PKDD/ECML Workshops (2) 2019: 390-401 - [c170]Guilherme Londres, Nuno Filipe, João Gama:
Optimizing Waste Collection: A Data Mining Approach. PKDD/ECML Workshops (1) 2019: 570-578 - [e20]Guoliang Li, Jun Yang, João Gama, Juggapong Natwichai, Yongxin Tong:
Database Systems for Advanced Applications - 24th International Conference, DASFAA 2019, Chiang Mai, Thailand, April 22-25, 2019, Proceedings, Part I. Lecture Notes in Computer Science 11446, Springer 2019, ISBN 978-3-030-18575-6 [contents] - [e19]Guoliang Li, Jun Yang, João Gama, Juggapong Natwichai, Yongxin Tong:
Database Systems for Advanced Applications - 24th International Conference, DASFAA 2019, Chiang Mai, Thailand, April 22-25, 2019, Proceedings, Part II. Lecture Notes in Computer Science 11447, Springer 2019, ISBN 978-3-030-18578-7 [contents] - [e18]Guoliang Li, Jun Yang, João Gama, Juggapong Natwichai, Yongxin Tong:
Database Systems for Advanced Applications - 24th International Conference, DASFAA 2019, Chiang Mai, Thailand, April 22-25, 2019, Proceedings, Part III, and DASFAA 2019 International Workshops: BDMS, BDQM, and GDMA, Chiang Mai, Thailand, April 22-25, 2019, Proceedings. Lecture Notes in Computer Science 11448, Springer 2019, ISBN 978-3-030-18589-3 [contents] - [e17]Anna Monreale, Carlos Alzate, Michael Kamp, Yamuna Krishnamurthy, Daniel Paurat, Moamar Sayed Mouchaweh, Albert Bifet, João Gama, Rita P. Ribeiro:
ECML PKDD 2018 Workshops - DMLE 2018 and IoTStream 2018, Dublin, Ireland, September 10-14, 2018, Revised Selected Papers. Communications in Computer and Information Science 967, Springer 2019, ISBN 978-3-030-14879-9 [contents] - [i12]Thiago Andrade, João Gama:
Identifying Points of Interest and Similar Individuals from Raw GPS Data. CoRR abs/1904.09357 (2019) - [i11]Brais Cancela, Verónica Bolón-Canedo, Amparo Alonso-Betanzos, João Gama:
A scalable saliency-based Feature selection method with instance level information. CoRR abs/1904.13127 (2019) - [i10]Richard Hugh Moulton, Herna L. Viktor, Nathalie Japkowicz, João Gama:
Contextual One-Class Classification in Data Streams. CoRR abs/1907.04233 (2019) - [i9]Thiago Andrade, Brais Cancela, João Gama:
Mining Human Mobility Data to Discover Locations and Habits. CoRR abs/1909.11406 (2019) - 2018
- [j92]Sofia Fernandes, Hadi Fanaee-T, João Gama:
Dynamic graph summarization: a tensor decomposition approach. Data Min. Knowl. Discov. 32(5): 1397-1420 (2018) - [j91]João Vinagre, Alípio Mário Jorge, João Gama:
Online bagging for recommender systems. Expert Syst. J. Knowl. Eng. 35(4) (2018) - [j90]Ana Rita Nogueira, Carlos Abreu Ferreira, João Gama:
Improving acute kidney injury detection with conditional probabilities. Intell. Data Anal. 22(6): 1355-1374 (2018) - [j89]Pedro Pereira Rodrigues, João Araújo, João Gama, Luís M. B. Lopes:
A local algorithm to approximate the global clustering of streams generated in ubiquitous sensor networks. Int. J. Distributed Sens. Networks 14(10) (2018) - [j88]Pawel Matuszyk, João Vinagre, Myra Spiliopoulou, Alípio Mário Jorge, João Gama:
Forgetting techniques for stream-based matrix factorization in recommender systems. Knowl. Inf. Syst. 55(2): 275-304 (2018) - [j87]Juan Gabriel Colonna, João Gama, Eduardo Freire Nakamura:
A comparison of hierarchical multi-output recognition approaches for anuran classification. Mach. Learn. 107(11): 1651-1671 (2018) - [j86]Fabíola Souza F. Pereira, João Gama, Sandra de Amo, Gina M. B. Oliveira:
On analyzing user preference dynamics with temporal social networks. Mach. Learn. 107(11): 1745-1773 (2018) - [j85]Ricardo Sousa, João Gama:
Multi-label classification from high-speed data streams with adaptive model rules and random rules. Prog. Artif. Intell. 7(3): 177-187 (2018) - [j84]