A Distributed Online Learning Approach for Pattern Prediction over Movement Event Streams with Apache Flink
暂无分享,去创建一个
Georg Fuchs | Michael Mock | Elias Alevizos | Ehab Qadah | G. Fuchs | M. Mock | E. Alevizos | Ehab Qadah
[1] Feng Yan,et al. Distributed Autonomous Online Learning: Regrets and Intrinsic Privacy-Preserving Properties , 2010, IEEE Transactions on Knowledge and Data Engineering.
[2] Ohad Shamir,et al. Optimal Distributed Online Prediction Using Mini-Batches , 2010, J. Mach. Learn. Res..
[3] David Luckham,et al. The power of events - an introduction to complex event processing in distributed enterprise systems , 2002, RuleML.
[4] Alexander Artikis,et al. Event Forecasting with Pattern Markov Chains , 2017, DEBS.
[5] Tomasz Imielinski,et al. Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.
[6] Hans-Arno Jacobsen,et al. Predictive publish/subscribe matching , 2010, DEBS '10.
[7] G. Nuel. Pattern Markov chains: optimal Markov chain embedding through deterministic finite automata , 2008 .
[8] Seif Haridi,et al. Apache Flink™: Stream and Batch Processing in a Single Engine , 2015, IEEE Data Eng. Bull..
[9] Michael Kamp,et al. Communication-Efficient Distributed Online Learning with Kernels , 2016, ECML/PKDD.
[10] Boris Cule,et al. A pattern based predictor for event streams , 2015, Expert Syst. Appl..
[11] Nikos Pelekis,et al. Online event recognition from moving vessel trajectories , 2016, GeoInformatica.
[12] Assaf Schuster,et al. Communication-Efficient Distributed Online Prediction by Dynamic Model Synchronization , 2014, ECML/PKDD.
[13] Imrich Chlamtac,et al. Internet of things: Vision, applications and research challenges , 2012, Ad Hoc Networks.
[14] Heikki Mannila,et al. Discovery of Frequent Episodes in Event Sequences , 1997, Data Mining and Knowledge Discovery.
[15] Stan Matwin,et al. Knowledge-based clustering of ship trajectories using density-based approach , 2014, 2014 IEEE International Conference on Big Data (Big Data).
[16] Alessandro Margara,et al. Processing flows of information: From data stream to complex event processing , 2012, CSUR.
[17] Murat Kulahci,et al. Introduction to Time Series Analysis and Forecasting , 2008 .
[18] Nikos Pelekis,et al. Event Recognition for Maritime Surveillance , 2015, EDBT.
[19] Ricardo Vilalta,et al. Predicting rare events in temporal domains , 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..
[20] K. Simmonds,et al. The International Maritime Organization , 1994 .
[21] Lina Fahed,et al. Efficient Discovery of Episode Rules with a Minimal Antecedent and a Distant Consequent , 2014, IC3K.
[22] Lin Xiao,et al. Dual Averaging Methods for Regularized Stochastic Learning and Online Optimization , 2009, J. Mach. Learn. Res..
[23] Ryen W. White,et al. Stream prediction using a generative model based on frequent episodes in event sequences , 2008, KDD.
[24] Minos N. Garofalakis,et al. FERARI: A Prototype for Complex Event Processing over Streaming Multi-cloud Platforms , 2016, SIGMOD Conference.
[25] Nick Koudas,et al. TwitterMonitor: trend detection over the twitter stream , 2010, SIGMOD Conference.
[26] John Langford,et al. Slow Learners are Fast , 2009, NIPS.
[27] Michele Vespe,et al. Vessel Pattern Knowledge Discovery from AIS Data: A Framework for Anomaly Detection and Route Prediction , 2013, Entropy.
[28] T. W. Anderson,et al. Statistical Inference about Markov Chains , 1957 .