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ORCIDDetlef D. Nauck
- > Home > Persons > Detlef D. Nauck
Publications
- 2021
[c42]Naveed Khan
, Zeeshan Tariq, Aftab Ali, Sally I. McClean, Paul N. Taylor, Detlef D. Nauck:
Early Prediction of Complex Business Processes Using Association Rule Based Mining. RTIP2R 2021: 183-194- 2020
- [j17]Vidhyalakshmi Karthikeyan, Brahim Allan, Detlef D. Nauck, Miguel Rio:
Benchmarking Video Service Quality: Quantifying the Viewer Impact of Loss-Related Impairments. IEEE Trans. Netw. Serv. Manag. 17(3): 1640-1652 (2020) - 2019
- [c41]Chris Wrench, Frederic T. Stahl, Giuseppe Di Fatta, Vidhyalakshmi Karthikeyan, Detlef D. Nauck:
A Rule Induction Approach to Forecasting Critical Alarms in a Telecommunication Network. ICDM Workshops 2019: 480-489 - [c40]Mariana Marasoiu, Detlef D. Nauck, Alan F. Blackwell:
Cuscus: An End User Programming Tool for Data Visualisation. IS-EUD 2019: 115-131 - [c38]Naveed Khan, Zulfiqar Ali, Aftab Ali, Sally I. McClean, Darryl Charles, Paul N. Taylor, Detlef D. Nauck:
A Generic Model for End State Prediction of Business Processes Towards Target Compliance. SGAI Conf. 2019: 325-335 - 2017
- [j16]Mai Le, Bogdan Gabrys, Detlef D. Nauck:
A hybrid model for business process event and outcome prediction. Expert Syst. J. Knowl. Eng. 34(5) (2017) - [c37]Vidhyalakshmi Karthikeyan, Detlef D. Nauck, Miguel Rio:
Using Machine Learning for Dynamic Multicast Capacity Planning. SGAI Conf. 2017: 417-422 - 2016
- [c36]Chris Wrench, Frederic T. Stahl, Thien Le, Giuseppe Di Fatta, Vidhyalakshmi Karthikeyan, Detlef D. Nauck:
A Method of Rule Induction for Predicting and Describing Future Alarms in a Telecommunication Network. SGAI Conf. 2016: 309-323 - [c35]David Sessler, Martin Spott, Detlef D. Nauck, William Harmer, Jörn Kohlhammer, Jürgen Bernard:
Towards Combining Attribute-based and Time Series-based Visual Querying. EuroVis (Posters) 2016: 73-75 - 2015
- [c34]Chris Wrench, Frederic T. Stahl, Giuseppe Di Fatta, Vidhyalakshmi Karthikeyan, Detlef D. Nauck:
Towards Expressive Rule Induction on IP Network Event Streams. SGAI Conf. 2015: 191-196 - 2014
- [j15]Abul Bashar, Gerard Parr, Sally I. McClean, Bryan W. Scotney, Detlef D. Nauck:
Application of Bayesian Networks for Autonomic Network Management. J. Netw. Syst. Manag. 22(2): 174-207 (2014) - [c33]Mai Le, Detlef D. Nauck, Bogdan Gabrys, Trevor Martin:
Sequential Clustering for Event Sequences and Its Impact on Next Process Step Prediction. IPMU (1) 2014: 168-178 - 2013
- [c32]Mai Le, Detlef D. Nauck, Bogdan Gabrys, Trevor Martin:
KNNs and Sequence Alignment for Churn Prediction. SGAI Conf. 2013: 279-285 - [c31]Mai Le, Detlef D. Nauck, Bogdan Gabrys:
Sequential Approaches for Predicting Business Process Outcome and Process Failure Warning. SIMPDA 2013: 1-15 - [p3]Martin Spott, Detlef D. Nauck, Paul N. Taylor:
Modern Analytics in Field and Service Operations. Transforming Field and Service Operations 2013: 85-99 - [i1]Rudolf Kruse, Detlef D. Nauck, Frank Klawonn:
Reasoning with Mass Distributions. CoRR abs/1303.5726 (2013) - 2012
- [c30]Abul Bashar, Gerard Parr, Sally I. McClean, Bryan W. Scotney, Detlef D. Nauck:
Performance analysis of Bayesian Networks-based distributed Call Admission Control for NGN. NOMS 2012: 1214-1220 - [c29]Mai Le, Bogdan Gabrys, Detlef D. Nauck:
A Hybrid Model for Business Process Event Prediction. SGAI Conf. 2012: 179-192 - 2011
- [c28]Abul Bashar, Gerard Parr, Sally I. McClean, Bryan W. Scotney, Detlef D. Nauck:
Novel distributed call admission control solution based on machine learning approach. Integrated Network Management 2011: 871-881 - 2010
- [c27]Abul Bashar, Gerard Parr, Sally I. McClean, Bryan W. Scotney, Detlef D. Nauck:
Machine learning based Call Admission Control approaches: A comparative study. CNSM 2010: 431-434 - [c26]Katharina Tschumitschew, Detlef D. Nauck, Frank Klawonn:
A Classification Algorithm for Process Sequences Based on Markov Chains and Bayesian Networks. KES (1) 2010: 141-147 - [c25]Abul Bashar, Gerard Parr, Sally I. McClean, Bryan W. Scotney, Detlef D. Nauck:
Knowledge Discovery Using Bayesian Network Framework for Intelligent Telecommunication Network Management. KSEM 2010: 518-529 - [c24]Abul Bashar, Gerard Parr, Sally I. McClean, Bryan W. Scotney, Detlef D. Nauck:
Learning-Based Call Admission Control Framework for QoS Management in Heterogeneous Networks. NDT (2) 2010: 99-111 - 2009
- [j14]Mirko Böttcher, Martin Spott, Detlef D. Nauck, Rudolf Kruse:
Mining changing customer segments in dynamic markets. Expert Syst. Appl. 36(1): 155-164 (2009) - [c23]Frank Klawonn, Detlef D. Nauck, Katharina Tschumitschew:
Measuring and Visualising Similarity of Customer Satisfaction Profiles for Different Customer Segments. HAIS 2009: 60-67 - 2008
- [p2]Martin Spott, Henry Abraham, Detlef D. Nauck:
Smart Data Analysis Services. Intelligent Techniques and Tools for Novel System Architectures 2008: 291-304 - 2007
- [j13]Xiaomeng Wang, Detlef D. Nauck, Martin Spott, Rudolf Kruse:
Intelligent data analysis with fuzzy decision trees. Soft Comput. 11(5): 439-457 (2007) - [c21]Mirko Böttcher, Martin Spott, Detlef D. Nauck:
A Framework for Discovering and Analyzing Changing Customer Segments. ICDM 2007: 255-268 - [c20]Georg Ruß, Detlef D. Nauck, Mirko Böttcher, Rudolf Kruse:
Relevance Feedback for Association Rules by Leveraging Concepts from Information Retrieval. SGAI Conf. 2007: 253-266 - 2006
- [j12]Martin Spott, Detlef D. Nauck:
Towards the automation of intelligent data analysis. Appl. Soft Comput. 6(4): 348-356 (2006) - [c19]Frank Klawonn, Detlef D. Nauck:
Automatically Determine Initial Fuzzy Partitions for Neuro-Fuzzy Classifiers. FUZZ-IEEE 2006: 1703-1709 - [c18]Dymitr Ruta, Detlef D. Nauck, Ben Azvine:
K Nearest Sequence Method and Its Application to Churn Prediction. IDEAL 2006: 207-215 - [c17]Mirko Böttcher, Detlef D. Nauck, Dymitr Ruta, Martin Spott:
Towards a Framework for Change Detection in Data Sets. SGAI Conf. 2006: 115-128 - [c16]Ben Azvine, Zhan Cui, Detlef D. Nauck, Basim A. Majeed:
Real Time Business Intelligence for the Adaptive Enterprise. CEC/EEE 2006: 29 - 2005
- [c15]Detlef D. Nauck, Martin Spott, Behnam Azvine:
Automatic Selection of Data Analysis Methods. ECSQARU 2005: 1014-1025 - [c14]Martin Spott, Detlef D. Nauck:
On Choosing an Appropriate Data Analysis Algorithm. FUZZ-IEEE 2005: 597-602 - [c13]Mirko Böttcher, Martin Spott, Detlef D. Nauck:
Detecting temporally redundant association rules. ICMLA 2005 - 2004
- [c12]Detlef D. Nauck, Martin Spott, Ben Azvine:
Fuzzy methods for automated intelligent data analysis. FUZZ-IEEE 2004: 487-492 - [c11]Beng-Seuk Lee, Trevor P. Martin, Nick P. Clarke, Basim A. Majeed, Detlef D. Nauck:
Dynamic Daily-Living Patterns and Association Analyses in Tele-Care Systems. ICDM 2004: 447-450 - 2003
- [b3]Christian Borgelt, Frank Klawonn, Rudolf Kruse, Detlef D. Nauck:
Neuro-Fuzzy-Systeme. Vieweg 2003, ISBN 978-3-528-25265-6, pp. 1-396 - 2001
- [p1]Detlef D. Nauck, Rudolf Kruse:
Information Fusion in Neuro-Fuzzy Systems. Data Fusion and Perception 2001: 77-90 - 2000
- [c9]Janusz Kacprzyk, Lotfi A. Zadeh, Ronald R. Yager, Donald H. Kraft, T. Whalen, Ernesto Damiani, T. Vila, Gabriella Pasi, Detlef D. Nauck:
Soft Computing Techniques for an Intelligent use of Internet Resources. FUZZ-IEEE 2000: 5-6 - [c7]Rudolf Kruse, Christian Borgelt, Detlef D. Nauck:
Problems and Prospects in Fuzzy Data Analysis. Intelligent Systems and Soft Computing 2000: 95-109 - [c6]Detlef D. Nauck, Rudolf Kruse:
NEFCLASS-J - A JAVA-Based Soft Computing Tool. Intelligent Systems and Soft Computing 2000: 139-160 - [e1]Behnam Azvine, Nader Azarmi, Detlef D. Nauck:
Intelligent Systems and Soft Computing: Prospects, Tools and Applications. Lecture Notes in Computer Science 1804, Springer 2000, ISBN 3-540-67837-9 [contents] - 1999
- [j6]Detlef D. Nauck, Rudolf Kruse:
Obtaining interpretable fuzzy classification rules from medical data. Artif. Intell. Medicine 16(2): 149-169 (1999) - [j5]Detlef D. Nauck, Rudolf Kruse:
Neuro-fuzzy systems for function approximation. Fuzzy Sets Syst. 101(2): 261-271 (1999) - 1998
- [j3]Andreas Nürnberger, Detlef D. Nauck, Rudolf Kruse:
Neuro-fuzzy control based on the NEFCON-model: recent developments. Soft Comput. 2(4): 168-182 (1998) - 1997
- [j2]Detlef D. Nauck, Rudolf Kruse:
A neuro-fuzzy method to learn fuzzy classification rules from data. Fuzzy Sets Syst. 89(3): 277-288 (1997) - [j1]Rudolf Kruse, Frank Klawonn, Detlef D. Nauck:
Erlerner von Fuzzy-Regeln. Inform. Forsch. Entwickl. 12(1): 2-6 (1997) - 1995
- [c5]Detlef D. Nauck, Rudolf Kruse:
NEFCLASSmdash;a neuro-fuzzy approach for the classification of data. SAC 1995: 461-465 - 1994
- [b2]Detlef D. Nauck, Frank Klawonn, Rudolf Kruse:
Neuronale Netze und Fuzzy-Systeme - Grundlagen des Konnektionismus, neuronaler Fuzzy-Systeme und der Kopplung mit wissensbasierten Methoden. Artificial intelligence - Künstliche Intelligenz, Vieweg 1994, ISBN 978-3-528-05265-2, pp. I-X, 1-407 - 1993
- [c4]Detlef D. Nauck, Rudolf Kruse:
A fuzzy neural network learning fuzzy control rules and membership functions by fuzzy error backpropagation. ICNN 1993: 1022-1027 - [c3]Detlef D. Nauck, Frank Klawonn, Rudolf Kruse:
Combining Neural Networks and Fuzzy Controllers. FLAI 1993: 35-46 - 1992
- [c2]Detlef D. Nauck, Frank Klawonn, Rudolf Kruse, Uwe Lohs:
Reasoning under Uncertainty with Temporal Aspects. IEA/AIE 1992: 572-580 - 1991
- [c1]Rudolf Kruse, Detlef D. Nauck, Frank Klawonn:
Reasoning with Mass Distributions. UAI 1991: 182-187
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