The following publications are possibly variants of this publication:
- Stream Data Mining Using the MOA FrameworkPhilipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer, Jesse Read. dasfaa 2012: 309-313 [doi]
- MOA: Massive Online Analysis, a Framework for Stream Classification and ClusteringAlbert Bifet, Geoff Holmes, Bernhard Pfahringer, Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl. jmlr, 11:44-50, 2010. [doi]
- Clustering Performance on Evolving Data Streams: Assessing Algorithms and Evaluation Measures within MOAPhilipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl, Albert Bifet, Geoff Holmes, Bernhard Pfahringer. icdm 2010: 1400-1403 [doi]
- MOA: A Real-Time Analytics Open Source FrameworkAlbert Bifet, Geoff Holmes, Bernhard Pfahringer, Jesse Read, Philipp Kranen, Hardy Kremer, Timm Jansen, Thomas Seidl. pkdd 2011: 617-620 [doi]
- Effective Evaluation Measures for Subspace Clustering of Data StreamsMarwan Hassani, Yunsu Kim, Seungjin Choi, Thomas Seidl. pakdd 2013: 342-353 [doi]