???global.info.a_carregar???
Albert Bifet. Is Full Professor in University of Waikato Department of Computer Science. Published 24 articles in journals. Has 23 book(s).
Identificação

Identificação pessoal

Nome completo
Albert Bifet

Nomes de citação

  • Bifet, Albert

Identificadores de autor

Ciência ID
8815-B67D-0DD8
ORCID iD
0000-0002-8339-7773
Percurso profissional

Docência no Ensino Superior

Categoria Profissional
Instituição de acolhimento 		Empregador
2019/02/04 - Atual Professor Catedrático (Docente Universitário) University of Waikato Department of Computer Science, Nova Zelândia
Produções

Publicações

Artigo em conferência
  1. Bifet, A.; Maniu, S.; Qian, J.; Tian, G.; He, C.; Fan, W.. "StreamDM: Advanced Data Mining in Spark Streaming". 2016.
    10.1109/ICDMW.2015.140
  2. Mayo, M.; Bifet, A.. "Deferral classification of evolving temporal dependent data streams". 2016.
    10.1145/2851613.2851890
  3. Morales, G.D.F.; Bifet, A.; Khan, L.; Gama, J.; Fan, W.. "IoT big data stream mining". 2016.
    10.1145/2939672.2945385
  4. Bifet, A.; Oliver, N.. "Message from the MDM 2016 industrial track co-chairs". 2016.
    10.1109/MDM.2016.9
  5. Bifet, A.. "Mining internet of things (IoT) big data streams". 2016.
  6. Read, J.; Puurula, A.; Bifet, A.. "Multi-label Classification with Meta-Labels". 2015.
    10.1109/ICDM.2014.38
  7. Read, J.; Bifet, A.. "Data Stream Classification Using Random Feature Functions and Novel Method Combinations". 2015.
    10.1109/Trustcom.2015.585
  8. Vu, A.T.; De Francisci Morales, G.; Gama, J.; Bifet, A.. "Distributed Adaptive Model Rules for mining big data streams". 2015.
    10.1109/BigData.2014.7004251
  9. Bifet, A.; Morales, G.D.F.. "Big data stream learning with SAMOA". 2015.
    10.1109/ICDMW.2014.24
  10. Read, J.; Perez-Cruz, F.; Bifet, A.. "Deep learning in partially-labeled data streams". 2015.
    10.1145/2695664.2695871
  11. Bifet, A.; De Francisci Morales, G.; Read, J.; Holmes, G.; Pfahringer, B.. "Efficient online evaluation of big data stream classifiers". 2015.
    10.1145/2783258.2783372
  12. Parker, B.S.; Khan, L.; Bifet, A.. "Incremental ensemble classifier addressing non-stationary fast data streams". 2015.
    10.1109/ICDMW.2014.116
  13. Sakthithasan, S.; Pears, R.; Bifet, A.; Pfahringer, B.. "Use of ensembles of Fourier spectra in capturing recurrent concepts in data streams". 2015.
    10.1109/IJCNN.2015.7280583
  14. Bifet, A.. "Real-time big data stream analytics". 2015.
  15. Rodrigues, P.P.; Bifet, A.; Krishnaswamy, S.; Gama, J.. "Special track on data streams". 2015.
  16. Ienco, D.; Bifet, A.; Pfahringer, B.; Poncelet, P.. "Change detection in categorical evolving data streams". 2014.
    10.1145/2554850.2554864
  17. Ienco, D.; Bifet, A.; Pfahringer, B.; Poncelet, P.. "Détection De Changements Dans Des Flots De Données Qualitatives". 2014.
  18. Bifet, A.; Read, J.; Pfahringer, B.; Holmes, G.. "Efficient data stream classification via probabilistic adaptive windows". 2013.
    10.1145/2480362.2480516
  19. Fan, W.; Bifet, A.; Yang, Q.; Yu, P.. "Preface". 2013.
  20. Rodrigues, P.P.; Bifet, A.; Krishnaswamy, S.; Gama, J.. "Special track on data streams". 2013.
  21. Rodrigues, P.P.; Bifet, A.; Krishnaswamy, S.; Gama, J.. "Editorial message: Special track on data streams". 2012.
  22. Fan, W.; Bifet, A.; Yang, Q.; Yu, P.. "Preface". 2012.
  23. Khan, L.; Pechenizkiy, M.; Zliobaite, I.; Agrawal, C.; Bifet, A.; Delany, S.J.; Dries, A.; et al. "Preface". 2011.
    10.1109/ICDMW.2011.195
  24. Bifet, A.; Holmes, G.; Pfahringer, B.; Gavaldà, R.. "Mining frequent closed graphs on evolving data streams". 2011.
    10.1145/2020408.2020501
  25. Kremer, H.; Kranen, P.; Jansen, T.; Seidl, T.; Bifet, A.; Holmes, G.; Pfahringer, B.. "An effective evaluation measure for clustering on evolving data streams". 2011.
    10.1145/2020408.2020555
  26. Kranen, P.; Kremer, H.; Jansen, T.; Seidl, T.; Bifet, A.; Holmes, G.; Pfahringer, B.. "Clustering performance on evolving data streams: Assessing algorithms and evaluation measures within MOA". 2010.
    10.1109/ICDMW.2010.17
  27. Bifet, A.; Holmes, G.; Pfahringer, B.; Kirkby, R.; Gavaldà, R.. "New ensemble methods for evolving data streams". 2009.
    10.1145/1557019.1557041
  28. Bifet, A.; Gavaldà, R.. "Mining adaptively frequent closed unlabeled rooted trees in data streams". 2008.
    10.1145/1401890.1401900
  29. Bifet, A.; Gavaldà, R.. "Learning from time-changing data with adaptive windowing". 2007.
  30. Balcázar, J.L.; Bifet, A.; Lozano, A.. "Subtree testing and closed tree mining through natural representations". 2007.
    10.1109/DEXA.2007.73
  31. Bifet, A.; Castillo, C.; Chirita, P.-A.; Weber, I.. "An analysis of factors used in search engine ranking". 2005.
Artigo em revista
  1. Jean Paul Barddal; Fabrício Enembreck; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer. "Boosting decision stumps for dynamic feature selection on data streams". Information Systems 83 (2019): 13-29. https://doi.org/10.1016%2Fj.is.2019.02.003.
    10.1016/j.is.2019.02.003
  2. Rodrigo F. de Mello; Yule Vaz; Carlos H. Grossi; Albert Bifet. "On learning guarantees to unsupervised concept drift detection on data streams". Expert Systems with Applications 117 (2019): 90-102. https://doi.org/10.1016%2Fj.eswa.2018.08.054.
    10.1016/j.eswa.2018.08.054
  3. Jean Paul Barddal; Fabrício Enembreck; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer. "Merit-guided dynamic feature selection filter for data streams". Expert Systems with Applications 116 (2019): 227-242. https://doi.org/10.1016%2Fj.eswa.2018.09.031.
    10.1016/j.eswa.2018.09.031
  4. Abhik Ray; Lawrence B. Holder; Albert Bifet. "Efficient frequent subgraph mining on large streaming graphs". Intelligent Data Analysis 23 1 (2019): 103-132. https://doi.org/10.3233%2Fida-173705.
    10.3233/ida-173705
  5. Pinghui Wang; Feiyang Sun; Di Wang; Jing Tao; Xiaohong Guan; Albert Bifet. "Predicting attributes and friends of mobile users from AP-Trajectories". Information Sciences 463-464 (2018): 110-128. https://doi.org/10.1016%2Fj.ins.2018.06.029.
    10.1016/j.ins.2018.06.029
  6. Mostafa Haghir Chehreghani; Albert Bifet; Talel Abdessalem. "Discriminative Distance-Based Network Indices with Application to Link Prediction". The Computer Journal 61 7 (2018): 998-1014. https://doi.org/10.1093%2Fcomjnl%2Fbxy040.
    10.1093/comjnl/bxy040
  7. Heitor Murilo Gomes; Jean Paul Barddal; Fabrício Enembreck; Albert Bifet. "A Survey on Ensemble Learning for Data Stream Classification". ACM Computing Surveys 50 2 (2017): 1-36. https://doi.org/10.1145%2F3054925.
    10.1145/3054925
  8. João Duarte; João Gama; Albert Bifet. "Adaptive Model Rules From High-Speed Data Streams". ACM Transactions on Knowledge Discovery from Data 10 3 (2016): 1-22. https://doi.org/10.1145%2F2829955.
    10.1145/2829955
  9. Carela-Español, V.; Barlet-Ros, P.; Bifet, A.; Fukuda, K.. "A streaming flow-based technique for traffic classification applied to 12 + 1 years of Internet traffic". Telecommunication Systems 63 2 (2016): 191-204. http://www.scopus.com/inward/record.url?eid=2-s2.0-84947553583&partnerID=MN8TOARS.
    10.1007/s11235-015-0114-6
  10. Quadrana, M.; Bifet, A.; Gavaldà, R.. "An efficient closed frequent itemset miner for the MOA stream mining system". AI Communications 28 1 (2015): 143-158. http://www.scopus.com/inward/record.url?eid=2-s2.0-84918509085&partnerID=MN8TOARS.
    10.3233/AIC-140615
  11. Marrón, D.; Read, J.; Bifet, A.; Navarro, N.. "Data stream classification using random feature functions and novel method combinations". Journal of Systems and Software (2015): http://www.scopus.com/inward/record.url?eid=2-s2.0-85006469957&partnerID=MN8TOARS.
    10.1016/j.jss.2016.06.009
  12. De Francisci Morales, G.; Bifet, A.. "SAMOA: Scalable advanced massive online analysis". Journal of Machine Learning Research 16 (2015): 149-153. http://www.scopus.com/inward/record.url?eid=2-s2.0-84923923168&partnerID=MN8TOARS.
  13. Žliobaite, I.; Bifet, A.; Read, J.; Pfahringer, B.; Holmes, G.. "Evaluation methods and decision theory for classification of streaming data with temporal dependence". Machine Learning 98 3 (2014): 455-482. http://www.scopus.com/inward/record.url?eid=2-s2.0-84922337645&partnerID=MN8TOARS.
    10.1007/s10994-014-5441-4
  14. Gama, J.; Zliobaite, I.; Bifet, A.; Pechenizkiy, M.; Bouchachia, A.. "A survey on concept drift adaptation". ACM Computing Surveys 46 4 (2014): http://www.scopus.com/inward/record.url?eid=2-s2.0-84901228061&partnerID=MN8TOARS.
    10.1145/2523813
  15. Zliobaite, I.; Bifet, A.; Pfahringer, B.; Holmes, G.. "Active learning with drifting streaming data". IEEE Transactions on Neural Networks and Learning Systems 25 1 (2014): 27-39. http://www.scopus.com/inward/record.url?eid=2-s2.0-84891134709&partnerID=MN8TOARS.
    10.1109/TNNLS.2012.2236570
  16. Wei Fan; Albert Bifet. "Mining big data". ACM SIGKDD Explorations Newsletter 14 2 (2013): 1-1. https://doi.org/10.1145%2F2481244.2481246.
    10.1145/2481244.2481246
  17. Bifet, A.. "Mining big data in real time". Informatica (Slovenia) 37 1 (2013): 15-20. http://www.scopus.com/inward/record.url?eid=2-s2.0-84877045865&partnerID=MN8TOARS.
  18. Read, J.; Bifet, A.; Holmes, G.; Pfahringer, B.. "Scalable and efficient multi-label classification for evolving data streams". Machine Learning 88 1-2 (2012): 243-272. http://www.scopus.com/inward/record.url?eid=2-s2.0-84865207305&partnerID=MN8TOARS.
    10.1007/s10994-012-5279-6
  19. Bifet, A.; Frank, E.; Holmes, G.; Pfahringer, B.. "Ensembles of restricted Hoeffding trees". ACM Transactions on Intelligent Systems and Technology 3 2 (2012): http://www.scopus.com/inward/record.url?eid=2-s2.0-84858171410&partnerID=MN8TOARS.
    10.1145/2089094.2089106
  20. Bifet, A.; Gavaldà, R.. "Mining frequent closed trees in evolving data streams". Intelligent Data Analysis 15 1 (2011): 29-48. http://www.scopus.com/inward/record.url?eid=2-s2.0-79551513583&partnerID=MN8TOARS.
    10.3233/IDA-2010-0454
  21. Bifet, A.; Frank, E.; Holmes, G.; Pfahringer, B.. "Accurate ensembles for data streams: Combining restricted hoeffding trees using stacking". Journal of Machine Learning Research 13 (2010): 225-240. http://www.scopus.com/inward/record.url?eid=2-s2.0-84864924228&partnerID=MN8TOARS.
  22. Bifet, A.; Holmes, G.; Kirkby, R.; Pfahringer, B.. "MOA: Massive Online Analysis". Journal of Machine Learning Research 11 (2010): 1601-1604. http://www.scopus.com/inward/record.url?eid=2-s2.0-77953527363&partnerID=MN8TOARS.
  23. Balcázar, J.L.; Bifet, A.; Lozano, A.. "Mining frequent closed rooted trees". Machine Learning 78 1-2 (2010): 1-33. http://www.scopus.com/inward/record.url?eid=2-s2.0-77952430648&partnerID=MN8TOARS.
    10.1007/s10994-009-5123-9
  24. Albert Bifet. "Adaptive learning and mining for data streams and frequent patterns". ACM SIGKDD Explorations Newsletter 11 1 (2009): 55-55. https://doi.org/10.1145%2F1656274.1656287.
    10.1145/1656274.1656287
Livro
  1. Barddal, J.P.; Gomes, H.M.; Enembreck, F.; Pfahringer, B.; Bifet, A.. On dynamic feature weighting for feature drifting data streams. 2016.
    10.1007/978-3-319-46227-1_9
  2. Huang, D.T.J.; Koh, Y.S.; Dobbie, G.; Bifet, A.. Drift detection using stream volatility. 2015.
    10.1007/978-3-319-23528-8_26
  3. Marron, D.; Bifet, A.; De Francisci Morales, G.. Random forests of very fast decision trees on GPU for mining evolving big data streams. 2014.
    10.3233/978-1-61499-419-0-615
  4. Bifet, A.; Read, J.; Žliobaite, I.; Pfahringer, B.; Holmes, G.. Pitfalls in benchmarking data stream classification and how to avoid them. 2013.
    10.1007/978-3-642-40988-2_30
  5. Bifet, A.; Read, J.; Pfahringer, B.; Holmes, G.; Žliobaite, I.. CD-MOA: Change detection framework for massive online analysis. 2013.
    10.1007/978-3-642-41398-8_9
  6. Quadrana, M.; Bifet, A.; Gavaldà, R.. An efficient closed frequent itemset miner for the moa stream mining system. 2013.
    10.3233/978-1-61499-320-9-203
  7. Ienco, D.; Bifet, A.; Žliobaite, I.; Pfahringer, B.. Clustering based active learning for evolving data streams. 2013.
    10.1007/978-3-642-40897-7_6
  8. Read, J.; Bifet, A.; Pfahringer, B.; Holmes, G.. Batch-incremental versus instance-incremental learning in dynamic and evolving data. 2012.
    10.1007/978-3-642-34156-4_29
  9. Kranen, P.; Kremer, H.; Jansen, T.; Seidl, T.; Bifet, A.; Holmes, G.; Pfahringer, B.; Read, J.. Stream data mining using the MOA framework. 2012.
    10.1007/978-3-642-29035-0_27
  10. Žliobaite, I.; Bifet, A.; Pfahringer, B.; Holmes, G.. Active learning with evolving streaming data. 2011.
    10.1007/978-3-642-23808-6_39
  11. Bifet, A.; Holmes, G.; Pfahringer, B.; Read, J.; Kranen, P.; Kremer, H.; Jansen, T.; Seidl, T.. MOA: A real-time analytics open source framework. 2011.
    10.1007/978-3-642-23808-6_41
  12. Bifet, A.; Holmes, G.; Pfahringer, B.. MOA-TweetReader: Real-time analysis in twitter streaming data. 2011.
    10.1007/978-3-642-24477-3_7
  13. Carmona-Cejudo, J.M.; Baena-García, M.; Del Campo-Ávila, J.; Bifet, A.; Gama, J.; Morales-Bueno, R.. Online evaluation of email streaming classifiers using GNUsmail. 2011.
    10.1007/978-3-642-24800-9_11
  14. Bifet, A.; Holmes, G.; Pfahringer, B.; Frank, E.. Fast perceptron decision tree learning from evolving data streams. 2010.
    10.1007/978-3-642-13672-6_30
  15. Bifet, A.; Frank, E.. Sentiment knowledge discovery in Twitter streaming data. 2010.
    10.1007/978-3-642-16184-1_1
  16. Carmona-Cejudo, J.M.; Baena-García, M.; Del Campo-Ávila, J.; Morales-Bueno, R.; Bifet, A.. GNUsmail: Open framework for on-line email classification. 2010.
    10.3233/978-1-60750-606-5-1141
  17. Bifet, A.; Holmes, G.; Pfahringer, B.. Leveraging bagging for evolving data streams. 2010.
    10.1007/978-3-642-15880-3_15
  18. Bifet, A.. Adaptive stream mining: Pattern learning and mining from evolving data streams. 2010.
    10.3233/978-1-60750-472-6-i
  19. Bifet, A.; Holmes, G.; Pfahringer, B.; Gavaldà, R.. Improving adaptive bagging methods for evolving data streams. 2009.
    10.1007/978-3-642-05224-8_4
  20. Bifet, A.; Gavaldà, R.. Adaptive learning from evolving data streams. 2009.
    10.1007/978-3-642-03915-7_22
  21. Bifet, A.; Gavaldà, R.. Adaptive XML tree classification on evolving data streams. 2009.
    10.1007/978-3-642-04180-8_27
  22. Balcázar, J.L.; Bifet, A.; Lozano, A.. Mining frequent closed unordered trees through natural representations. 2007.
  23. Bifet, A.; Gavaldà, R.. Kalman filters and adaptive windows for learning in data streams. 2006.

Outros

Outra produção
  1. EXAD: A System for Explainable Anomaly Detection on Big Data Traces. 2018. Fei Song; Yanlei Diao; Jesse Read; Arnaud Stiegler; Albert Bifet. https://doi.org/10.1109%2Ficdmw.2018.00204.
    10.1109/icdmw.2018.00204
  2. Bitcoin Volatility Forecasting with a Glimpse into Buy and Sell Orders. 2018. Tian Guo; Albert Bifet; Nino Antulov-Fantulin. https://doi.org/10.1109%2Ficdm.2018.00123.
    10.1109/icdm.2018.00123
  3. Unsupervised real-time detection of BGP anomalies leveraging high-rate and fine-grained telemetry data. 2018. Andrian Putina; Steven Barth; Albert Bifet; Drew Pletcher; Cristina Precup; Patrice Nivaggioli; Dario Rossi. https://doi.org/10.1109%2Finfcomw.2018.8406838.
    10.1109/infcomw.2018.8406838
  4. DyBED: An Efficient Algorithm for Updating Betweenness Centrality in Directed Dynamic Graphs. 2018. Mostafa Haghir Chehreghani; Albert Bifet; Talel Abdessalem. https://doi.org/10.1109%2Fbigdata.2018.8622452.
    10.1109/bigdata.2018.8622452
  5. Ubiquitous Artificial Intelligence and Dynamic Data Streams. 2018. Albert Bifet; Jesse Read. https://doi.org/10.1145%2F3210284.3214345.
    10.1145/3210284.3214345
  6. Learning Fast and Slow: A Unified Batch/Stream Framework. 2018. Jacob Montiel; Albert Bifet; Viktor Losing; Jesse Read; Talel Abdessalem. https://doi.org/10.1109%2Fbigdata.2018.8622222.
    10.1109/bigdata.2018.8622222
  7. An In-depth Comparison of Group Betweenness Centrality Estimation Algorithms. 2018. Mostafa Haghir Chehreghani; Albert Bifet; Talel Abdessalem. https://doi.org/10.1109%2Fbigdata.2018.8622133.
    10.1109/bigdata.2018.8622133
  8. Telemetry-based stream-learning of BGP anomalies. 2018. Andrian Putina; Dario Rossi; Albert Bifet; Steven Barth; Drew Pletcher; Cristina Precup; Patrice Nivaggioli. https://doi.org/10.1145%2F3229607.3229611.
    10.1145/3229607.3229611
  9. Session details: Information systems: DS - data streams track. 2018. Albert Bifet; Andre Carvalho; Joao Gama. https://doi.org/10.1145%2F3167132.3258638.
    10.1145/3167132.3258638
  10. A Sketch-Based Naive Bayes Algorithms for Evolving Data Streams. 2018. Maroua Bahri; Silviu Maniu; Albert Bifet. https://doi.org/10.1109%2Fbigdata.2018.8622178.
    10.1109/bigdata.2018.8622178
  11. Inferring Demographics and Social Networks of Mobile Device Users on Campus From AP-Trajectories. 2017. Pinghui Wang; Feiyang Sun; Di Wang; Jing Tao; Xiaohong Guan; Albert Bifet. https://doi.org/10.1145%2F3041021.3054140.
    10.1145/3041021.3054140
  12. Low-latency multi-threaded ensemble learning for dynamic big data streams. 2017. Diego Marron; Eduard Ayguade; Jose R. Herrero; Jesse Read; Albert Bifet. https://doi.org/10.1109%2Fbigdata.2017.8257930.
    10.1109/bigdata.2017.8257930
  13. Extremely Fast Decision Tree Mining for Evolving Data Streams. 2017. Albert Bifet; Jiajin Zhang; Wei Fan; Cheng He; Jianfeng Zhang; Jianfeng Qian; Geoff Holmes; Bernhard Pfahringer. https://doi.org/10.1145%2F3097983.3098139.
    10.1145/3097983.3098139
  14. Predicting over-indebtedness on batch and streaming data. 2017. Jacob Montiel; Albert Bifet; Talel Abdessalem. https://doi.org/10.1109%2Fbigdata.2017.8258084.
    10.1109/bigdata.2017.8258084
  15. VHT: Vertical hoeffding tree. 2016. Nicolas Kourtellis; Gianmarco De Francisci Morales; Albert Bifet; Arinto Murdopo. https://doi.org/10.1109%2Fbigdata.2016.7840687.
    10.1109/bigdata.2016.7840687
  16. Data Stream Classification Using Random Feature Functions and Novel Method Combinations. 2015. Jesse Read; Albert Bifet. https://doi.org/10.1109%2Ftrustcom.2015.585.
    10.1109/trustcom.2015.585
  17. Multi-label Classification with Meta-Labels. 2014. Jesse Read; Antti Puurula; Albert Bifet. https://doi.org/10.1109%2Ficdm.2014.38.
    10.1109/icdm.2014.38
  18. Incremental Ensemble Classifier Addressing Non-stationary Fast Data Streams. 2014. Brandon S. Parker; Latifur Khan; Albert Bifet. https://doi.org/10.1109%2Ficdmw.2014.116.
    10.1109/icdmw.2014.116
  19. Big Data Stream Learning with SAMOA. 2014. Albert Bifet; Gianmarco De Francisci Morales. https://doi.org/10.1109%2Ficdmw.2014.24.
    10.1109/icdmw.2014.24
  20. Learning from Time-Changing Data with Adaptive Windowing. 2013. Albert Bifet; Ricard Gavaldà. https://doi.org/10.1137%2F1.9781611972771.42.
    10.1137/1.9781611972771.42