Journal ArticleDOI
Advances in data stream mining
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This paper reviews key milestones and state of the art in the data stream mining area and future insights are presented.Abstract:
Mining data streams has been a focal point of research interest over the past decade. Hardware and software advances have contributed to the significance of this area of research by introducing faster than ever data generation. This rapidly generated data has been termed as data streams. Credit card transactions, Google searches, phone calls in a city, and many others are typical data streams. In many important applications, it is inevitable to analyze this streaming data in real time. Traditional data mining techniques have fallen short in addressing the needs of data stream mining. Randomization, approximation, and adaptation have been used extensively in developing new techniques or adopting exiting ones to enable them to operate in a streaming environment. This paper reviews key milestones and state of the art in the data stream mining area. Future insights are also be presented.read more
Citations
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A survey on data preprocessing for data stream mining
TL;DR: This survey summarizes, categorize and analyze those contributions on data preprocessing that cope with streaming data, and takes into account the existing relationships between the different families of methods (feature and instance selection, and discretization).
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Fifty years of pulsar candidate selection: from simple filters to a new principled real-time classification approach
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Data mining tools
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Journal ArticleDOI
Kappa Updated Ensemble for drifting data stream mining
Alberto Cano,Bartosz Krawczyk +1 more
TL;DR: KUE is a combination of online and block-based ensemble approaches that uses Kappa statistic for dynamic weighting and selection of base classifiers and is capable of outperforming state-of-the-art ensembles on standard and imbalanced drifting data streams while having a low computational complexity.
References
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Proceedings ArticleDOI
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Proceedings ArticleDOI
Mining high-speed data streams
Pedro Domingos,Geoff Hulten +1 more
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Proceedings ArticleDOI
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