Frank Höppner

66 papers A 1B 19C 3Journal 11Unranked 24

Year	Rank	Type	Title / Venue / Authors
2025	B	`conf`	Local Embedding Consensus Across Multiple Descriptor Spaces. KES Lea Eileen Brauner, Frank Höppner
2024	C	`conf`	Adaptivity of Card Recommendation Systems for Legends of Code and Magic. CoG Timo Haumann, Frank Höppner
2024	—	`conf`	Estimating and Differentiating Programming Skills from Unstructured Coding Exercises via Matrix Factorization. Koli Calling Fabian Pfütsch, Frank Höppner
2023	—	`conf`	Enhancing Computer Science Education by Automated Analysis of Students' Code Submissions. ECAI Workshops (2) Lea Eileen Brauner, Frank Höppner
2022	B	`conf`	Is there Method in Your Mistakes? Capturing Error Contexts by Graph Mining for Targeted Feedback. EDM Maximilian Jahnke, Frank Höppner
2021	B	`conf`	Grouping Source Code by Solution Approaches - Improving Feedback in Programming Courses. EDM Frank Höppner
2020	B	`conf`	Enriched Weisfeiler-Lehman Kernel for Improved Graph Clustering of Source Code. IDA Frank Höppner, Maximilian Jahnke
2020	—	`book`	Guide to Intelligent Data Science - How to Intelligently Make Use of Real Data, Second Edition Michael R. Berthold, Christian Borgelt, Frank Höppner, Frank Klawonn, Rosaria Silipo
2020	B	`conf`	Multidimensional Decision Tree Splits to Improve Interpretability. KES Frank Höppner
2020	—	`conf`	Taking benefit from fellow students code without copying off - making better use of students collective work. DeLFI Frank Höppner
2019	—	`conf`	Generating "Who Wants to Be a Millionaire?" Questions Sets Automatically from Wikidata. SEMANTiCS (Posters & Demos) Markus Wohlan, Yannik Schröder, Frank Höppner
2019	—	`conf`	Holistic Assessment of Structure Discovery Capabilities of Clustering Algorithms. ECML/PKDD (1) Frank Höppner, Maximilian Jahnke
2019	B	`conf`	Measuring Instruction Comprehension by Mining Memory Traces for Early Formative Feedback in Java Courses. ITiCSE Frank Höppner
2018	—	`conf`	Zur automatischen Erkennung von Fehlkonzepten bei Java-Einsteigern durch Analyse von Speicher-Protokollen. DeLFI Frank Höppner, Jan-Hendrik Hemmje
2017	—	`conf`	A Multiscale Bezier-Representation for Time Series that Supports Elastic Matching. ECML/PKDD (2) Frank Höppner, Tobias Sobek
2017	J	`jnl`	Improving time series similarity measures by integrating preprocessing steps. Data Min. Knowl. Discov. Frank Höppner
2017	—	`conf`	Internalizing a Viable Mental Model of Program Execution in First Year Programming Courses. ABP Robin Goltermann, Frank Höppner
2016	J	`jnl`	On Clustering Time Series Using Euclidean Distance and Pearson Correlation. CoRR Michael R. Berthold, Frank Höppner
2016	B	`conf`	Visual Perception of Discriminative Landmarks in Classified Time Series. IDA Tobias Sobek, Frank Höppner
2015	C	`conf`	Optimal Filtering for Time Series Classification. IDEAL Frank Höppner
2015	—	`conf`	Zur Einschätzung von Programmierfähigkeiten - Jedem Programmieranfänger über die Schultern schauen. ABP Bastian Schulten, Frank Höppner
2014	B	`conf`	A subspace filter supporting the discovery of small clusters in very noisy datasets. SSDBM Frank Höppner
2014	—	`conf`	Efficient Identification of Subspaces with Small but Substantive Clusters in Noisy Datasets. LWA Frank Höppner
2014	B	`conf`	Finding the Intrinsic Patterns in a Collection of Time Series. IDA Anke Schweier, Frank Höppner
2014	A	`conf`	Less is More: Similarity of Time Series under Linear Transformations. SDM Frank Höppner
2014	J	`jnl`	Temporal interval pattern languages to characterize time flow. WIREs Data Mining Knowl. Discov. Frank Höppner, Sebastian Peter
2013	B	`ed.`	Advances in Intelligent Data Analysis XII - 12th International Symposium, IDA 2013, London, UK, October 17-19, 2013. Proceedings IDA Allan Tucker, Frank Höppner, Arno Siebes, Stephen Swift
2013	—	`conf`	Pattern Graphs: Combining Multivariate Time Series and Labelled Interval Sequences for Classification. SGAI Conf. Sebastian Peter, Frank Höppner, Michael R. Berthold
2012	B	`conf`	Learning Pattern Graphs for Multivariate Temporal Pattern Retrieval. IDA Sebastian Peter, Frank Höppner, Michael R. Berthold
2012	—	`conf`	Pattern graphs: A knowledge-based tool for multivariate temporal pattern retrieval. IEEE Conf. of Intelligent Systems Sebastian Peter, Frank Höppner, Michael R. Berthold
2012	—	`conf`	What are Clusters in High Dimensions and are they Difficult to Find? CHDD Frank Klawonn, Frank Höppner, Balasubramaniam Jayaram
2011	B	`conf`	An Alternative to ROC and AUC Analysis of Classifiers. IDA Frank Klawonn, Frank Höppner, Sigrun May
2010	—	`ch.`	Association Rules. Data Mining and Knowledge Discovery Handbook Frank Höppner
2010	—	`conf`	Finding Temporal Patterns Using Constraints on (Partial) Absence, Presence and Duration. KES (1) Sebastian Peter, Frank Höppner
2010	—	`book`	Guide to Intelligent Data Analysis - How to Intelligently Make Sense of Real Data. Michael R. Berthold, Christian Borgelt, Frank Höppner, Frank Klawonn
2010	J	`jnl`	Learning in parallel universes. Data Min. Knowl. Discov. Bernd Wiswedel, Frank Höppner, Michael R. Berthold
2009	B	`conf`	Compensation of Translational Displacement in Time Series Clustering Using Cross Correlation. IDA Frank Höppner, Frank Klawonn
2009	—	`ch.`	Fuzzy Cluster Analysis of Larger Data Sets. Scalable Fuzzy Algorithms for Data Management and Analysis Roland Winkler, Frank Klawonn, Frank Höppner, Rudolf Kruse
2009	—	`conf`	How Much MLDM Frank Höppner
2008	—	`ch.`	Clustering with Size Constraints. Computational Intelligence Paradigms Frank Höppner, Frank Klawonn
2008	J	`jnl`	On exploiting the power of time in data mining. SIGKDD Explor. Mirko Böttcher, Frank Höppner, Myra Spiliopoulou
2007	C	`conf`	Classification Based on the Trace of Variables over Time. IDEAL Frank Höppner, Alexander Topp
2007	—	`book`	Einführung in die Softwareentwicklung - vom Programmieren zur erfolgreichen Software-Projektarbeit: am Beispiel von Java und C++. Hartmut Helmke, Frank Höppner, Rolf Isernhagen
2007	B	`conf`	Landscape Multidimensional Scaling. IDA Katharina Tschumitschew, Frank Klawonn, Frank Höppner, Vitaliy Kolodyazhniy
2007	—	`conf`	Matching Partitions over Time to Reliably Capture Local Clusters in Noisy Domains. PKDD Frank Höppner, Mirko Böttcher
2007	—	`conf`	Reliably Capture Local Clusters in Noisy Domains From Parallel Universes. Parallel Universes and Local Patterns Frank Höppner, Mirko Böttcher
2006	—	`conf`	Equi-sized, Homogeneous Partitioning. KES (2) Frank Klawonn, Frank Höppner
2005	—	`ch.`	Association Rules. The Data Mining and Knowledge Discovery Handbook Frank Höppner
2005	—	`conf`	Objective Function-based Discretization. GfKl Frank Höppner
2004	J	`jnl`	Fuzzy information granules in time series data. Int. J. Intell. Syst. Michael R. Berthold, Marco Ortolani, David E. Patterson, Frank Höppner, Ondine Callan, Heiko Hofer
2004	—	`conf`	Local Pattern Detection and Clustering. Local Pattern Detection Frank Höppner
2003	J	`jnl`	A contribution to convergence theory of fuzzy c-means and derivatives. IEEE Trans. Fuzzy Syst. Frank Höppner, Frank Klawonn
2003	—	`conf`	An alternative approach to the fuzzifier in fuzzy clustering to obtain better clustering. EUSFLAT Conf. Frank Klawonn, Frank Höppner
2003	J	`jnl`	Improved fuzzy partitions for fuzzy regression models. Int. J. Approx. Reason. Frank Höppner, Frank Klawonn
2003	—	`—`	Knowledge discovery from sequential data. Frank Höppner
2003	B	`conf`	What Is Fuzzy about Fuzzy Clustering? Understanding and Improving the Concept of the Fuzzifier. IDA Frank Klawonn, Frank Höppner
2002	—	`conf`	Discovery of Core Episodes from Sequences. Pattern Detection and Discovery Frank Höppner
2002	J	`jnl`	Finding informative rules in interval sequences. Intell. Data Anal. Frank Höppner, Frank Klawonn
2002	B	`conf`	Fuzzy information granules in time series data. FUZZ-IEEE Marco Ortolani, Heiko Hofer, David E. Patterson, Frank Höppner, Michael R. Berthold
2002	B	`conf`	Handling Feature Ambiguity in Knowledge Discovery from Time Series. Discovery Science Frank Höppner
2002	J	`jnl`	Learning indistinguishability from data. Soft Comput. Frank Höppner, Frank Klawonn, Patrik Eklund
2002	J	`jnl`	Speeding up fuzzy c-means: using a hierarchical data organisation to control the precision of membership calculation. Fuzzy Sets Syst. Frank Höppner
2002	—	`conf`	Time Series Abstraction Methods - A Survey. GI Jahrestagung Frank Höppner
2001	—	`conf`	Discovery of Temporal Patterns. Learning Rules about the Qualitative Behaviour of Time Series. PKDD Frank Höppner
2001	B	`conf`	Finding Informative Rules in Interval Sequences. IDA Frank Höppner, Frank Klawonn
2000	B	`conf`	Obtaining interpretable fuzzy models from fuzzy clustering and fuzzy regression. KES Frank Höppner, Frank Klawonn