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Albert Bifet. Is Full Professor in University of Waikato Department of Computer Science. Published 24 articles in journals. Has 23 book(s).
Identification

Personal identification

Full name
Albert Bifet

Citation names

  • Bifet, Albert

Author identifiers

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

Teaching in Higher Education

Category
Host institution 		Employer
2019/02/04 - Current Full Professor (University Teacher) University of Waikato Department of Computer Science, New Zealand
Outputs

Publications

Book
  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.
Conference paper
  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.
Journal article
  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

Other

Other output
  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