Frank Höppner

According to our database1, Frank Höppner authored at least 58 papers between 2000 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2020
Guide to Intelligent Data Science - How to Intelligently Make Use of Real Data, Second Edition
Texts in Computer Science, Springer, ISBN: 978-3-030-45573-6, 2020

Multidimensional Decision Tree Splits to Improve Interpretability.
Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 24th International Conference KES-2020, 2020

Enriched Weisfeiler-Lehman Kernel for Improved Graph Clustering of Source Code.
Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

Taking benefit from fellow students code without copying off - making better use of students collective work.
Proceedings of the DELFI 2020, 2020

2019
Holistic Assessment of Structure Discovery Capabilities of Clustering Algorithms.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Measuring Instruction Comprehension by Mining Memory Traces for Early Formative Feedback in Java Courses.
Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education, 2019

Generating "Who Wants to Be a Millionaire?" Questions Sets Automatically from Wikidata.
Proceedings of the Posters and Demo Track of the 15th International Conference on Semantic Systems co-located with 15th International Conference on Semantic Systems (SEMANTiCS 2019), Karlsruhe, Germany, September 9th - to, 2019

2018
Zur automatischen Erkennung von Fehlkonzepten bei Java-Einsteigern durch Analyse von Speicher-Protokollen.
Proceedings of the DeLFI 2018, 2018

2017
Improving time series similarity measures by integrating preprocessing steps.
Data Min. Knowl. Discov., 2017

A Multiscale Bezier-Representation for Time Series that Supports Elastic Matching.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Internalizing a Viable Mental Model of Program Execution in First Year Programming Courses.
Proceedings of the Third Workshop "Automatische Bewertung von Programmieraufgaben" (ABP 2017), 2017

2016
On Clustering Time Series Using Euclidean Distance and Pearson Correlation.
CoRR, 2016

Visual Perception of Discriminative Landmarks in Classified Time Series.
Proceedings of the Advances in Intelligent Data Analysis XV - 15th International Symposium, 2016

2015
Optimal Filtering for Time Series Classification.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2015, 2015

Zur Einschätzung von Programmierfähigkeiten - Jedem Programmieranfänger über die Schultern schauen.
Proceedings of the Second Workshop "Automatische Bewertung von Programmieraufgaben", 2015

2014
Temporal interval pattern languages to characterize time flow.
Wiley Interdiscip. Rev. Data Min. Knowl. Discov., 2014

A subspace filter supporting the discovery of small clusters in very noisy datasets.
Proceedings of the Conference on Scientific and Statistical Database Management, 2014

Less is More: Similarity of Time Series under Linear Transformations.
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Efficient Identification of Subspaces with Small but Substantive Clusters in Noisy Datasets.
Proceedings of the 16th LWA Workshops: KDML, 2014

Finding the Intrinsic Patterns in a Collection of Time Series.
Proceedings of the Advances in Intelligent Data Analysis XIII, 2014

2013
Pattern Graphs: Combining Multivariate Time Series and Labelled Interval Sequences for Classification.
Proceedings of the Research and Development in Intelligent Systems XXX, 2013

2012
Pattern graphs: A knowledge-based tool for multivariate temporal pattern retrieval.
Proceedings of the 6th IEEE International Conference on Intelligent Systems, 2012

Learning Pattern Graphs for Multivariate Temporal Pattern Retrieval.
Proceedings of the Advances in Intelligent Data Analysis XI - 11th International Symposium, 2012

What are Clusters in High Dimensions and are they Difficult to Find?
Proceedings of the Clustering High-Dimensional Data - First International Workshop, 2012

2011
An Alternative to ROC and AUC Analysis of Classifiers.
Proceedings of the Advances in Intelligent Data Analysis X - 10th International Symposium, 2011

2010
Guide to Intelligent Data Analysis - How to Intelligently Make Sense of Real Data.
Texts in Computer Science 42, Springer, ISBN: 978-1-84882-260-3, 2010

Association Rules.
Proceedings of the Data Mining and Knowledge Discovery Handbook, 2nd ed., 2010

Learning in parallel universes.
Data Min. Knowl. Discov., 2010

Finding Temporal Patterns Using Constraints on (Partial) Absence, Presence and Duration.
Proceedings of the Knowledge-Based and Intelligent Information and Engineering Systems, 2010

2009
How Much <i>True</i> Structure Has Been Discovered?
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2009

Compensation of Translational Displacement in Time Series Clustering Using Cross Correlation.
Proceedings of the Advances in Intelligent Data Analysis VIII, 2009

Fuzzy Cluster Analysis of Larger Data Sets.
Proceedings of the Scalable Fuzzy Algorithms for Data Management and Analysis, 2009

2008
Clustering with Size Constraints.
Proceedings of the Computational Intelligence Paradigms, Innovative Applications, 2008

On exploiting the power of time in data mining.
SIGKDD Explor., 2008

2007
Matching Partitions over Time to Reliably Capture Local Clusters in Noisy Domains.
Proceedings of the Knowledge Discovery in Databases: PKDD 2007, 2007

Classification Based on the Trace of Variables over Time.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2007

Landscape Multidimensional Scaling.
Proceedings of the Advances in Intelligent Data Analysis VII, 2007

Reliably Capture Local Clusters in Noisy Domains From Parallel Universes.
Proceedings of the Parallel Universes and Local Patterns, 01.05. - 04.05.2007, 2007

Einführung in die Softwareentwicklung - vom Programmieren zur erfolgreichen Software-Projektarbeit: am Beispiel von Java und C++.
Hanser, 2007

2006
Equi-sized, Homogeneous Partitioning.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2006

2005
Objective Function-based Discretization.
Proceedings of the From Data and Information Analysis to Knowledge Engineering, 2005

Association Rules.
Proceedings of the Data Mining and Knowledge Discovery Handbook., 2005

2004
Fuzzy information granules in time series data.
Int. J. Intell. Syst., 2004

Local Pattern Detection and Clustering.
Proceedings of the Local Pattern Detection, 2004

2003
Knowledge discovery from sequential data.
PhD thesis, 2003

A contribution to convergence theory of fuzzy c-means and derivatives.
IEEE Trans. Fuzzy Syst., 2003

Improved fuzzy partitions for fuzzy regression models.
Int. J. Approx. Reason., 2003

What Is Fuzzy about Fuzzy Clustering? Understanding and Improving the Concept of the Fuzzifier.
Proceedings of the Advances in Intelligent Data Analysis V, 2003

An alternative approach to the fuzzifier in fuzzy clustering to obtain better clustering.
Proceedings of the 3rd Conference of the European Society for Fuzzy Logic and Technology, 2003

2002
Learning indistinguishability from data.
Soft Comput., 2002

Finding informative rules in interval sequences.
Intell. Data Anal., 2002

Speeding up fuzzy c-means: using a hierarchical data organisation to control the precision of membership calculation.
Fuzzy Sets Syst., 2002

Time Series Abstraction Methods - A Survey.
Proceedings of the 32. Jahrestagung der Gesellschaft für Informatik, Informatik bewegt, INFORMATIK 2002, Dortmund, Germany, September 30, 2002

Fuzzy information granules in time series data.
Proceedings of the 2002 IEEE International Conference on Fuzzy Systems, 2002

Discovery of Core Episodes from Sequences.
Proceedings of the Pattern Detection and Discovery, 2002

Handling Feature Ambiguity in Knowledge Discovery from Time Series.
Proceedings of the Discovery Science, 5th International Conference, 2002

2001
Discovery of Temporal Patterns. Learning Rules about the Qualitative Behaviour of Time Series.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2001

2000
Obtaining interpretable fuzzy models from fuzzy clustering and fuzzy regression.
Proceedings of the Fourth International Conference on Knowledge-Based Intelligent Information Engineering Systems & Allied Technologies, 2000


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