Christian Borgelt

Christian Borgelt, Christian Braune, Tobias Kötter, Sonja Grün: New algorithms for finding approximate frequent item sets. Soft Comput. 16(5): 903-917 (2012)

Christian Borgelt: Frequent item set mining. Wiley Interdisc. Rew.: Data Mining and Knowledge Discovery 2(6): 437-456 (2012)

Christian Braune, Christian Borgelt, Sonja Grün: Assembly Detection in Continuous Neural Spike Train Data. IDA 2012: 78-89

David Picado-Muiño, Iván Castro León, Christian Borgelt: Fuzzy Frequent Pattern Mining in Spike Trains. IDA 2012: 289-300

Christian Borgelt: Soft Pattern Mining in Neuroscience. SMPS 2012: 3-10

Christian Borgelt, Xiaoyuan Yang, Rubén Nogales-Cadenas, Pedro Carmona-Saez, Alberto D. Pascual-Montano: Finding closed frequent item sets by intersecting transactions. EDBT 2011: 367-376

Gyözö Gidófalvi, Manohar Kaul, Christian Borgelt, Torben Bach Pedersen: Frequent route based continuous moving object location- and density prediction on road networks. GIS 2011: 381-384

Christian Borgelt, Tobias Kötter: Mining Fault-Tolerant Item Sets Using Subset Size Occurrence Distributions. IDA 2011: 43-54

Christian Braune, Christian Borgelt, Sonja Grün: Finding Ensembles of Neurons in Spike Trains by Non-linear Mapping and Statistical Testing. IDA 2011: 55-66

Marc Segond, Christian Borgelt: Item Set Mining Based on Cover Similarity. PAKDD (2) 2011: 493-505

Denise Berger, Christian Borgelt, Sebastien Louis, Abigail Morrison, Sonja Grün: Efficient Identification of Assembly Neurons within Massively Parallel Spike Trains. Comp. Int. and Neurosc. 2010 (2010)

Christian Borgelt: A conditional independence algorithm for learning undirected graphical models. J. Comput. Syst. Sci. 76(1): 21-33 (2010)

Sebastien Louis, Christian Borgelt, Sonja Grün: Complexity distribution as a measure for assembly size and temporal precision. Neural Networks 23(6): 705-712 (2010)

Marc Segond, Christian Borgelt: Selecting the Links in BisoNets Generated from Document Collections. IDA 2010: 196-207

Christian Borgelt: Simple Algorithms for Frequent Item Set Mining. Advances in Machine Learning II 2010: 351-369

Christian Borgelt: Accelerating fuzzy clustering. Inf. Sci. 179(23): 3985-3997 (2009)

Christian Borgelt, Xiaomeng Wang: SaM: A Split and Merge Algorithm for Fuzzy Frequent Item Set Mining. IFSA/EUSFLAT Conf. 2009: 968-973

Sonja Grün, Denise Berger, Christian Borgelt: Identification of neurons participating in cell assemblies. ICASSP 2009: 3493-3496

Christian Borgelt, Thorsten Meinl: Full Perfect Extension Pruning for Frequent Subgraph Mining. Mining Complex Data 2009: 189-205

Magdalene G. Borgelt, Christian Borgelt, Christos Levcopoulos: Fixed Parameter Algorithms for the Minimum Weight Triangulation Problem. Int. J. Comput. Geometry Appl. 18(3): 185-220 (2008)

Christian Borgelt: Feature weighting and feature selection in fuzzy clustering. FUZZ-IEEE 2008: 838-844

Christian Borgelt: Fuzzy Subspace Clustering. GfKl 2008: 93-103

Christian Borgelt: Resampling for Fuzzy Clustering. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 15(5): 595-614 (2007)

Christian Borgelt: Prototype-less Fuzzy Clustering. FUZZ-IEEE 2007: 1-6

Christian Borgelt: Learning Undirected Possibilistic Networks with Conditional Independence Tests. FUZZ-IEEE 2007: 1-6

Christian Borgelt, Gil Gonzáles-Rodríguez: FrIDA - A Free Intelligent Data Analysis Toolbox. FUZZ-IEEE 2007: 1-5

Christian Borgelt, Mathias Fiedler: Graph Mining: Repository vs. Canonical Form. GfKl 2007: 229-236

Mathias Fiedler, Christian Borgelt: Subgraph Support in a Single Large Graph. ICDM Workshops 2007: 399-404

Mathias Fiedler, Christian Borgelt: Support Computation for Mining Frequent Subgraphs in a Single Graph. MLG 2007

Christian Borgelt: Canonical Forms for Frequent Graph Mining. GfKl 2006: 337-349

Christian Borgelt, Thorsten Meinl: Full Perfect Extension Pruning for Frequent Graph Mining. ICDM Workshops 2006: 263-268

Myra Spiliopoulou, Rudolf Kruse, Christian Borgelt, Andreas Nürnberger, Wolfgang Gaul (Eds.): From Data and Information Analysis to Knowledge Engineering, Proceedings of the 29th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Magdeburg, March 9-11, 2005. Studies in Classification, Data Analysis, and Knowledge Organization, Springer 2006, isbn 978-3-540-31313-7

Christian Borgelt, Rudolf Kruse: Probabilistic Graphical Models for the Diagnosis of Analog Electrical Circuits. ECSQARU 2005: 100-110

Christian Borgelt, Michael R. Berthold, David E. Patterson: Molecular Fragment Mining for Drug Discovery. ECSQARU 2005: 1002-1013

Xiaomeng Wang, Christian Borgelt, Rudolf Kruse: Fuzzy frequent pattern discovering based on recursive elimination. ICMLA 2005

Magdalene Grantson, Christian Borgelt, Christos Levcopoulos: Minimum Weight Triangulation by Cutting Out Triangles. ISAAC 2005: 984-994

Christian Borgelt, Rudolf Kruse: Probabilistische grafische Modellle und ihre Anwendung in der Automobilindustrie. Datenbank-Spektrum 9: 18-23 (2004)

Heiko Timm, Christian Borgelt, Christian Döring, Rudolf Kruse: An extension to possibilistic fuzzy cluster analysis. Fuzzy Sets and Systems 147(1): 3-16 (2004)

Heiko Hofer, Christian Borgelt, Michael R. Berthold: Large scale mining of molecular fragments with wildcards. Intell. Data Anal. 8(5): 495-504 (2004)

Christian Borgelt: Recursion Pruning for the Apriori Algorithm. FIMI 2004

Christian Borgelt, Daniela Girimonte, Giuseppe Acciani: Modeling and diagnosis of analog circuits with probabilistic graphical models. ISCAS (4) 2004: 485-488

Christian Borgelt, Daniela Girimonte, Giuseppe Acciani: Learning vector quantization: cluster size and cluster number. ISCAS (5) 2004: 808-811

Christian Borgelt, Andreas Nürnberger: Experiments in Term Weighting and Keyword Extraction in Document Clustering. LWA 2004: 123-130

Christian Borgelt, Rudolf Kruse: Shape and Size Regularization in Expectation Maximization and Fuzzy Clustering. PKDD 2004: 52-62

Christian Borgelt, Thorsten Meinl, Michael R. Berthold: Advanced pruning strategies to speed up mining closed molecular fragments. SMC (5) 2004: 4565-4570

Christian Borgelt, Rudolf Kruse: Operations and evaluation measures for learning possibilistic graphical models. Artif. Intell. 148(1-2): 385-418 (2003)

Rudolf Kruse, Christian Borgelt: Information mining. Int. J. Approx. Reasoning 32(2-3): 63-65 (2003)

Christian Borgelt, Rudolf Kruse: Learning possibilistic graphical models from data. IEEE T. Fuzzy Systems 11(2): 159-172 (2003)

Heiko Hofer, Christian Borgelt, Michael R. Berthold: Large Scale Mining of Molecular Fragments with Wildcards. IDA 2003: 376-385

Christian Borgelt: On Identifying Tree-Structured Perfect Maps. KI 2003: 385-395

Michael R. Berthold, Hans-Joachim Lenz, Elizabeth Bradley, Rudolf Kruse, Christian Borgelt (Eds.): Advances in Intelligent Data Analysis V, 5th International Symposium on Intelligent Data Analysis, IDA 2003, Berlin, Germany, August 28-30, 2003, Proceedings. Lecture Notes in Computer Science 2810, Springer 2003, isbn 3-540-40813-4

Christian Borgelt, Rudolf Kruse: Graphical models - methods for data analysis and mining. Wiley 2002, isbn 978-0-470-84337-6, pp. I-VIII, 1-358

Rudolf Kruse, Christian Borgelt: Data Mining with Graphical Models. ALT 2002: 22

Rudolf Kruse, Christian Borgelt: Data Mining with Graphical Models. Discovery Science 2002: 2-11

Christian Borgelt, Michael R. Berthold: Mining Molecular Fragments: Finding Relevant Substructures of Molecules. ICDM 2002: 51-58

Christian Borgelt, Rudolf Kruse: Unsicherheit und Vagheit: Begriffe, Methoden, Forschungsthemen. KI 15(3): 5-8 (2001)

Christian Borgelt, Rudolf Kruse: Unsicherheit und Vagheit - Serviceteil. KI 15(3): 48 (2001)

Christian Borgelt, Rudolf Kruse: An Empirical Investigation of the K2 Metric. ECSQARU 2001: 240-251

Christian Borgelt, Rudolf Kruse: Learning Graphical Models With Hypertree Structure Using a Simulated Annealing Approach. FUZZ-IEEE 2001: 135-138

Rudolf Kruse, Christian Borgelt, Detlef Nauck: Problems and Prospects in Fuzzy Data Analysis. Intelligent Systems and Soft Computing 2000: 95-109

Christian Borgelt, Heiko Timm: Advanced Fuzzy Clustering and Decision Tree Plug-Ins for Data Engine^TM. Intelligent Systems and Soft Computing 2000: 188-212

Christian Borgelt, Rudolf Kruse: A Critique of Inductive Causation. ESCQARU 1999: 68-79

Christian Borgelt, Rudolf Kruse, Guido Lindner: Lernen probabilistischer und possibilistischer Netze aus Daten: Theorie und Anwendung. KI 12(1): 11-17 (1998)

Rudolf Kruse, Christian Borgelt: Data Mining with Graphical Models. KI 1998: 3-16

Christian Borgelt, Rudolf Kruse: Some Experimental Results on Learning Probabilistic and Possibilistic Networks with Different Evaluation Measures. ECSQARU-FAPR 1997: 71-85