Moa: Massive online analysis, a framework for stream classification and clustering A Bifet, G Holmes, B Pfahringer, P Kranen, H Kremer, T Jansen, T Seidl Proceedings of the first workshop on applications of pattern analysis, 44-50, 2010 | 2301 | 2010 |
An introduction to computational networks and the computational network toolkit D Yu, A Eversole, M Seltzer, K Yao, Z Huang, B Guenter, O Kuchaiev, ... Microsoft Technical Report MSR-TR-2014–112, 2014 | 476 | 2014 |
The clustree: indexing micro-clusters for anytime stream mining P Kranen, I Assent, C Baldauf, T Seidl Knowledge and information systems 29, 249-272, 2011 | 351 | 2011 |
An effective evaluation measure for clustering on evolving data streams H Kremer, P Kranen, T Jansen, T Seidl, A Bifet, G Holmes, B Pfahringer Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 139 | 2011 |
Anyout: Anytime outlier detection on streaming data I Assent, P Kranen, C Baldauf, T Seidl Database Systems for Advanced Applications: 17th International Conference …, 2012 | 134 | 2012 |
Self-adaptive anytime stream clustering P Kranen, I Assent, C Baldauf, T Seidl 2009 Ninth IEEE International Conference on Data Mining, 249-258, 2009 | 91 | 2009 |
Efficient emd-based similarity search in multimedia databases via flexible dimensionality reduction M Wichterich, I Assent, P Kranen, T Seidl Proceedings of the 2008 ACM SIGMOD international conference on Management of …, 2008 | 77 | 2008 |
MOA: a real-time analytics open source framework A Bifet, G Holmes, B Pfahringer, J Read, P Kranen, H Kremer, T Jansen, ... Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011 | 70 | 2011 |
Indexing density models for incremental learning and anytime classification on data streams T Seidl, I Assent, P Kranen, R Krieger, J Herrmann Proceedings of the 12th international conference on extending database …, 2009 | 69 | 2009 |
Harnessing the strengths of anytime algorithms for constant data streams P Kranen, T Seidl Data Mining and Knowledge Discovery 19, 245-260, 2009 | 41 | 2009 |
Clustering performance on evolving data streams: Assessing algorithms and evaluation measures within moa P Kranen, H Kremer, T Jansen, T Seidl, A Bifet, G Holmes, B Pfahringer 2010 IEEE International Conference on Data Mining Workshops, 1400-1403, 2010 | 33 | 2010 |
Stream data mining using the MOA framework P Kranen, H Kremer, T Jansen, T Seidl, A Bifet, G Holmes, B Pfahringer, ... Database Systems for Advanced Applications: 17th International Conference …, 2012 | 32 | 2012 |
Pipeline generation for data stream actuated control ADB De Septfontaines, M Cozowicz, P Kranen, T Santen US Patent App. 14/573,866, 2016 | 30 | 2016 |
Massive online analysis manual A Bifet, R Kirkby, P Kranen, P Reutemann University of Waikato, New Zealand: Centre for Open Software Innovation 11 …, 2009 | 30 | 2009 |
Precise anytime clustering of noisy sensor data with logarithmic complexity M Hassani, P Kranen, T Seidl Proceedings of the Fifth International Workshop on Knowledge Discovery from …, 2011 | 28 | 2011 |
Subspace anytime stream clustering M Hassani, P Kranen, R Saini, T Seidl Proceedings of the 26th International Conference on Scientific and …, 2014 | 20 | 2014 |
MC-tree: Improving bayesian anytime classification P Kranen, S Günnemann, S Fries, T Seidl Scientific and Statistical Database Management: 22nd International …, 2010 | 20 | 2010 |
Mobile mining and information management in healthnet scenarios P Kranen, D Kensche, S Kim, N Zimmermann, E Müller, C Quix, X Li, ... The Ninth International Conference on Mobile Data Management (mdm 2008), 215-216, 2008 | 17 | 2008 |
Detection of anomalies in error signals of cloud based service O Ivanova, S Ojha, A De Baynast, M Cozowicz, U Pinsdorf, Y Wang, ... US Patent 9,378,079, 2016 | 14 | 2016 |
BT*–An Advanced Algorithm for Anytime Classification P Kranen, M Hassani, T Seidl International Conference on Scientific and Statistical Database Management …, 2012 | 11 | 2012 |