| Knowledge fusion for probabilistic generative classifiers with data mining applications D Fisch, E Kalkowski, B Sick IEEE Transactions on Knowledge and Data Engineering 26 (3), 652-666, 2013 | 48 | 2013 |
| Learning from others: Exchange of classification rules in intelligent distributed systems D Fisch, M Jänicke, E Kalkowski, B Sick Artificial Intelligence 187, 90-114, 2012 | 32 | 2012 |
| Techniques for knowledge acquisition in dynamically changing environments D Fisch, M Jänicke, E Kalkowski, B Sick ACM Transactions on Autonomous and Adaptive Systems (TAAS) 7 (1), 16, 2012 | 29 | 2012 |
| In your interest-objective interestingness measures for a generative classifier D Fisch, E Kalkowski, B Sick, SJ Ovaska International Conference on Agents and Artificial Intelligence 2, 414-423, 2011 | 19 | 2011 |
| Collaborative learning by knowledge exchange D Fisch, E Kalkowski, B Sick Organic Computing—A Paradigm Shift for Complex Systems, 267-280, 2011 | 17 | 2011 |
| Learning by teaching versus learning by doing: Knowledge exchange in organic agent systems D Fisch, M Janicke, E Kalkowski, B Sick 2009 IEEE Symposium on Intelligent Agents, 31-38, 2009 | 13 | 2009 |
| Towards automation of knowledge understanding: An approach for probabilistic generative classifiers D Fisch, C Gruhl, E Kalkowski, B Sick, SJ Ovaska Information Sciences 370, 476-496, 2016 | 5 | 2016 |
| Correlation of Ontology-Based Semantic Similarity and Human Judgement for a Domain Specific Fashion Ontology E Kalkowski, B Sick Web Engineering: 16th International Conference, ICWE 2016, Lugano …, 2016 | 2 | 2016 |
| Using ontology-based similarity measures to find training data for problems with sparse data E Kalkowski, B Sick 2015 IEEE International Conference on Systems, Man, and Cybernetics, 1693-1699, 2015 | 1 | 2015 |
| Generative Vorhersagetechniken für Raten und Ontologie-basierte Ähnlichkeitsberechnung mit Anwendungen im Suchmaschinenmarketing E Kalkowski kassel university press GmbH, 2019 | | 2019 |
| Generative Exponential Smoothing and Generative ARMA Models to Forecast Time-Variant Rates or Probabilities E Kalkowski, B Sick Time Series Analysis and Forecasting: Selected Contributions from the ITISE …, 2016 | | 2016 |
| Self-Extending Training Sets: Using Ontologies to Improve Machine Learning Performance E Kalkowski Organic Computing: Doctoral Dissertation Colloquium 2014 4, 111, 2014 | | 2014 |
