Fields of Interest
My fields of interests in the area of data mining and machine
learning are
Publication List
Books
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H. Helmke, F. Höppner, R. Isernhagen:
Einführung in die Softwareentwicklung.
Hanser, München, 2007.
- F. Höppner, F. Klawonn, R. Kruse, T. Runkler:
Fuzzy Cluster Analysis.
Wiley, Chichester, 1999.
- F. Höppner, F. Klawonn, R. Kruse:
Fuzzy-Clusteranalyse:
Verfahren für die Bilderkennung, Klassifikation und Datenanalyse.
Reihe Computational Intelligence, Vieweg, Braunschweig, 1997.
Journal Papers and Book Chapters
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M. Böttcher, F. Höppner, M. Spiliopoulou:
On exploiting the power of time in data mining
SIGKDD Explorations 10(2): 3-11 (2008)
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F. Höppner, F. Klawonn:
Clustering with Size Constraints
In: Computational Intelligence Paradigms, Springer, 2008.
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F. Höppner:
Association Rules
In: O. Maimon, L. Rokach (eds.):
The Data Mining and Knowledge Discovery Handbook.
© Springer, Berlin (2005): 353-376
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F. Höppner, F. Klawonn:
Learning Fuzzy Systems -- An Objective-Function Approach.
Mathware and Soft Computing Journal, 11(5) 2004, 143--162
- F. Höppner, F. Klawonn:
A Contribution to Convergence Theory of Fuzzy c-Means and Derivatives.
IEEE Trans. on Fuzzy Systems, 11(5), pp. 682-694, 2003.
- F. Höppner, F. Klawonn:
Improved Fuzzy Partitions for Fuzzy Regression Models.
International Journal of Approximate Reasoning (32), 85-102, 2003.
- F. Höppner, F. Klawonn:
Finding Informative Rules in Interval Sequences.
Intelligent Data Analysis - An International Journal, 6(3), 237-256, 2002.
- F. Höppner, F. Klawonn:
Learning Rules about the Development of Variables over Time.
In: C.T. Leondes (editor): Intelligent Systems -
Techniques and Applications, vol IV, CRC Press, 201-228, 2002.
- F. Höppner:
Speeding up Fuzzy c-Means: Using a Hierarchical Data Organisation to Control the Precision of Membership Calculation.
Fuzzy Sets and Systems, 128(3), pp. 365-378, 2002.
- F. Höppner, F. Klawonn, P. Eklund:
Learning Indistinguishability from Data.
Soft Computing Journal 6(1), pp. 6-13, 2002
- F. Höppner:
Fuzzy Shell Clustering Algorithms in Image Processing: Fuzzy c-Rectangular and 2-Rectangular Shells.
IEEE Transactions on Fuzzy Systems, 5(4), pp. 599-613, 1997.
Conference and Workshop Papers
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F. Höppner, F. Klawonn:
Compensation of Translational Displacement in Time Series Clustering Using Cross Correlation
In: Proc. 8th Int. Symp. Intelligent Data Analyis (IDA) (2009), 71-82, © Springer
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F. Höppner:
How much true structure has been discovered? -- Validating Explorative Clustering on a Hold-Out Test Set
In: Proc. Machine Learning and Data Mining in Pattern Recognition (MLDM) (2009), 385--397, © Springer
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F. Höppner, A. Topp:
Classification Based on the Trace of Variables over Time.
Proc. Int. Conf. Intelligent Data Engineering and Automated Learning (IDEAL) (2007), 739--749
© Springer
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F. Höppner, M. Böttcher:
Matching Partitions over Time to Reliably Capture Local Clusters in Noisy Domains.
Proc. Int. Conf. Principles and Practice of Knowledge Discovery in Databases PKDD (2007), 479-486
[ .pdf ]
© Springer
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K. Tschumitschew, F. Klawonn, F. Höppner, V. Kolodyazhniy:
Landscape Multidimensional Scaling.
Proc. Symp. on Intelligent Data Analysis (IDA) (2007), 263-273,
© Springer.
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F. Höppner:
Klassifikation von Zeitreihen und Sequenzen.
Proc. 16th Workshop Computational Intelligence (2006), 179-189
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F. Höppner, F. Klawonn:
Visualising Clusters in High-Dimensional Data Sets by Intersecting Spheres.
Proc. International Symposium on
Evolving Fuzzy Systems (2006), 106-111
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F. Klawonn, F. Höppner:
Equi-sized, Homogeneous Partitioning.
Int. Conf. on Knowledge-Based Intelligent Engineering Systems and Allied Technologies, Springer LNCS 4252 (2006), 70-77
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© Springer
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F. Höppner:
Objective Function-Based Discretization.
Proc. 29th Annual Conf. of the Gesellschaft für Klassifikation,
Springer, Berlin (2005): 483-445
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F. Höppner:
Local Pattern Detection and Clustering -- Are there substantive differences?
In: K. Morik, J.-F. Boulicaut, A. Siebes (eds.):
Local Pattern Detection © Springer, Berlin (2005): 53-70
[ .pdf ]
© Springer
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F. Klawonn, F. Höppner:
An Alternative Approach to the Fuzzifier in Fuzzy Clustering to Obtain
Better Clustering Results.
In: Proceedings 3rd Eusflat. EUSFLAT, Zittau (2003), 730-734
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F. Klawonn, F. Höppner:
What is Fuzzy About Fuzzy Clustering? -- Understanding and Improving the Concept of the Fuzzifier.
In: M.R. Berthold, H.-J. Lenz, E. Bradley, R. Kruse, C. Borgelt (eds.):
Advances in Intelligent Data Analysis V. © Springer, Berlin (2003), 254-264
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© Springer
- F. Höppner:
Handling feature ambiguity in knowledge discovery from time series.
In Proc. of the Int. Conf. on Discovery Science, LNCS 2534,
pp. 398-405. Lübeck, Germany, 2002.
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© Springer
- F. Höppner:
Time series abstraction methods -- A Survey.
Tagungsband zur 32. GI Jahrestagung 2002, Workshop on Knowledge Discovery
in Databases, Dortmund, pp. 777-786, Sept/Okt. 2002.
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- F. Höppner:
Discovery of core episodes from sequences -- using generalization for defragmentation of rule sets.
In Pattern Detection and Discovery in Data Mining, LNAI 2447, pp. 199-213.
London, England, Sept 2002.
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© Springer
- F. Höppner:
Learning Dependencies in Multivariate Time Series.
Proc. of the ECAI'02 Workshop on Knowledge Discovery in (Spatio-)
Temporal Data, Lyon, France, pp. 25-31, July 2002.
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- F. Höppner:
Lernen lokaler Zusammenhänge in multivariaten Zeitreihen.
Tagungsband zum 5. Göttinger Symposium Soft Computing,
Göttingen, pp. 113-125, Juni 2002.
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- M. Ortolani, H. Hofer, D. Patterson, F. Höppner and M. Berthold:
Fuzzy Information Granules in Time Series Data.
Proc. of IEEE Int. Conf. on Fuzzy Systems,
Honolulu, Hawai, pp. 695-699, May 2002.
- F. Höppner, F. Klawonn:
Finding Informative Rules in Interval Sequences.
Advances in Intelligent Data Analysis,
Proc. of the 4th International Symposium,
Lecture Notes in Computer Sciences 2189, Springer.
Lissabon, Portugal, pp. 123-132, Sept. 2001.
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© Springer
- F. Höppner:
Discovery of Temporal Patterns - Learning Rules about the Qualitative
Behaviour of Time Series.
Proc. of the 5th European Conference on Principles and Practice of Knowledge
Discovery in Databases, Lecture Notes in Artificial Intelligence 2168,
Springer. Freiburg, Germany, pp. 192-203, Sept. 2001.
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© Springer
- F. Höppner:
Learning Temporal Rules from State Sequences.
IJCAI Workshop on Learning from Temporal and Spatial Data,
Seattle, USA, pp. 25-31, 2001.
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- F. Höppner, F. Klawonn:
A New Approach to Fuzzy Partitioning.
Proc. of the Joint 9th IFSA World Congress and
20th NAFIPS International Conference,
Vancouver, Canada, pp. 1419-1424, 2001.
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- F. Höppner, F. Klawonn:
Obtaining Interpretable Fuzzy Models from Fuzzy Clustering and Fuzzy Regression.
Proc. of the 4th Int. Conf. on Knowledge-Based Intelligent Engineering
Systems and Allied Technologies (KES), Brighton, UK, pp. 162-165, 2000.
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- F. Höppner, F. Klawonn:
Fuzzy Clustering of Sampled Functions.
Proc. of the 19th Int. Conf. of the North American Fuzzy Information
Processing Society (NAFIPS), Atlanta, USA, pp. 251-255, 2000.
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- F. Höppner:
Piecewise Linear Function Approximation by Alternating Optimization.
Proc. of the 8th Int. Conf. on Information Processing and Management
of Uncertainty in Knowledge Based Systems (IPMU),
Madrid, Spain, pp. 1751-1757, 2000.
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