Philipp Kranen
Philipp Kranen
Microsoft Research
Verified email at microsoft.com
Title
Cited by
Cited by
Year
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
15162010
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
4082014
Preliminary Mariner 9 report on the geology of Mars
JF McCauley, MH Carr, JA Cutts, WK Hartmann, H Masursky, DJ Milton, ...
Icarus 17 (2), 289-327, 1972
3171972
The ClusTree: indexing micro-clusters for anytime stream mining
P Kranen, I Assent, C Baldauf, T Seidl
Knowledge and information systems 29 (2), 249-272, 2011
2602011
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
932011
Anyout: Anytime outlier detection on streaming data
I Assent, P Kranen, C Baldauf, T Seidl
International Conference on Database Systems for Advanced Applications, 228-242, 2012
902012
Self-adaptive anytime stream clustering
P Kranen, I Assent, C Baldauf, T Seidl
2009 Ninth IEEE International Conference on Data Mining, 249-258, 2009
782009
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
702008
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
572009
MOA: a real-time analytics open source framework
A Bifet, G Holmes, B Pfahringer, J Read, P Kranen, H Kremer, T Jansen, ...
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011
512011
Harnessing the strengths of anytime algorithms for constant data streams
P Kranen, T Seidl
Data Mining and Knowledge Discovery 19 (2), 245-260, 2009
362009
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
282010
Massive online analysis manual
A Bifet, R Kirkby, P Kranen, P Reutemann
University of Waikato, New Zealand: Centre for Open Software Innovation, 2009
272009
Stream data mining using the MOA framework
P Kranen, H Kremer, T Jansen, T Seidl, A Bifet, G Holmes, B Pfahringer, ...
International Conference on Database Systems for Advanced Applications, 309-313, 2012
222012
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
212011
MC-tree: Improving bayesian anytime classification
P Kranen, S Günnemann, S Fries, T Seidl
International Conference on Scientific and Statistical Database Management …, 2010
162010
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
162008
Subspace anytime stream clustering
M Hassani, P Kranen, R Saini, T Seidl
Proceedings of the 26th International Conference on Scientific and …, 2014
152014
Massive Online Analysis
A Bifet, R Kirkby, P Kranen, P Reutemann
Technical Manual, University of Waikato, 2009
102009
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
82016
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