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RealStream 2013 : Real-World Challenges for Data Stream Mining Workshop | |||||||||||||||
Link: https://sites.google.com/site/realstream2013 | |||||||||||||||
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Call For Papers | |||||||||||||||
CALL FOR WORKSHOP TALKS
Real-World Challenges for Data Stream Mining Workshop-Discussion at ECMLPKDD 2013 September 27th, 2013, Prague, Czech Republic https://sites.google.com/site/realstream2013/ * * * * * * * * * * * * * * * * * * * * * * * * FOCUS Data streams, online learning and adaptation to concept drift have become important research topics during the last decade. Data arrives in a stream in real time and needs to be mined in real time. In spite of the popularity of the research, truly autonomous, self-maintaining, adaptive data mining systems are rarely reported. This workshop will provide a forum for researchers and practitioners to discuss real-world challenges for data stream mining, identify gaps between data streams research and meaningful applications, and define new application-relevant research directions for data stream mining. CALL FOR PAPERS The focus of this workshop is on presentations and discussions rather than on full written articles. Only extended abstracts (up to 4 pages in Springer LNCS format) are required as a submission and will be published in the online proceedings. The submission of works-in-progress, industrial experiences, as well as the presentation of works already published elsewhere is strongly encouraged. Well articulated position papers are welcome. TOPICS OF INTEREST We invite contributions focusing on real world challenges for data stream mining. Topics include, but are not limited to: 1.Challenges and lessons learned from mining real-world data streams 2.Dealing with realistic data and workflows - End user participation to varying degrees - Interactive user feedback for adaptive learning - Reliability / correctness of feedback - Availability and delay of feedback 3.Integrating expert knowledge into data stream models - What to ask of an expert? - When to ask? How to set the priorities? 4.Moving from data stream algorithms towards data stream tools - Online data preparation and pre-processing - Improving usability and trust - Developing autonomous, self-diagnosing data stream tools 5.Scalability of data stream mining systems KEY DATES July 5, 2013: Extended abstract submission July 26, 2013: Notification of acceptance August 9, 2013: Camera-ready September 27, 2013: Workshop date ORGANIZATION Workshop organizers Georg Krempl, KMD, Otto-von-Guericke-University Magdeburg, Germany Indre Zliobaite, Aalto University, Finland Yin Wang, Facebook, USA George Forman, HP Labs, USA Program Committee Albert Bifet, Yahoo! Research, Spain Joao Gama, LIAAD - INESC Porto, University Porto T. Ryan Hoens, SAS Institute, USA Petr Kadlec, Evonik Industries, Germany Vincent Lemaire, Orange Labs, France Fabian Moerchen, Amazon, USA Mykola Pechenizkiy, TU Eindhoven, The Netherlands Myra Spiliopoulou, KMD, Otto-von-Guericke-University Magdeburg, Germany Alexey Tsymbal, Siemens, Germany (to be finalized) |
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