Prof. Dr. Michael Kaufmann Michael Kaufmann

Meier, Andreas & Kaufmann, Michael (2016). SQL- & NoSQL-Datenbanken. Berlin Heidelberg: Springer.

Kaufmann, Michael (2014). Inductive Fuzzy Classification in Marketing Analytics. Cham Heidelberg New York Dordrecht London: Springer International Publishing.

Kaufmann, Michael (2019). Big Data Management Canvas: A Reference Model for Value Creation from Data. Big Data and Cognitive Computing, 3(1), 19.

Kaufmann, Michael; Siegfried, Patrick; Huck, Lukas & Stettler, Jürg (2019). Analysis of Tourism Hotspot Behaviour Based on Geolocated Travel Blog Data: The Case of Qyer. ISPRS International Journal of Geo-Information, 2019(11), 493. doi: 10.3390/ijgi8110493

Mazzola, Luca; Siegfried, Patrick; Waldis, Andreas; Kaufmann, Michael & Denzler, Alexander (2018). A domain specific ESA inspired approach for document semantic description. Proceedings of the 2018 IEEE International Conference on Intelligent Systems (IS), nd.

Waldis, Andreas; Mazzola, Luca & Kaufmann, Michael (2018). Concept Extraction with Convolutional Neural Networks. Proceedings of the 7th International Conference on Data Science, Technology and Applications, 118-129.

Nawroth, Christian; Schmedding, Matthäus; Brocks, Holger; Kaufmann, Michael; Fuchs, Michael & Hemmje, Matthias (2015). Towards Cloud-Based Knowledge Capturing Based on Natural Language Processing. Procedia Computer Science, 5(68), 206-216. doi: 10.1016/j.procs.2015.09.236

Kaufmann, Michael; Meier, Andreas & Stoffel, Kilian (2015). IFC-Filter: Membership function generation for inductive fuzzy classification. Expert Systems with Applications, 21(42), 8369-8379.

Mazzola, Luca; Siegfried, Patrick; Waldis, Andreas; Stalder, Florian; Denzler, Alexander & Kaufmann, Michael (2020). A Domain Specific ESA Method for Semantic Text Matching. Intelligent Systems: Theory, Research and Innovation in Application (S. 25-49). Cham: Springer Nature Switzerland AG.

Waldis, Andreas; Mazzola, Luca & Kaufmann, Michael (2019). Concept Recognition with Convolutional Neural Networks to Optimize Keyphrase Extraction. In Quix C., Bernardino J. (eds) (Hrsg.), Data Management Technologies and Applications. DATA 2018. Communications in Computer and Information Science, vol 862. (S. 160-188). Cham: Springer Nature Switzerland AG.

Emmenegger, Sandro; Lutz, Jonas & Kaufmann, Michael (2016). Merging Bottom-Up and Top-Down Knowledge Graphs for Intuitive Knowledge Browsing. In Troels Andreasen; Henning Christiansen; Janusz Kacprzyk; Henrik Larsen; Gabriella Pasi; Olivier Pivert; Guy De Tré; Maria Amparo Vila; Adnan Yazici; Sławomir Zadrożny (Hrsg.), Flexible Query Answering Systems 2015 (S. 445-459). Cham Heidelberg New York Dordrecht London: Springer Verlag.

Kaufmann, Michael; Waldis, Andreas; Siegfried, Patrick; Wilke, Gwendolin; Portmann, Edy & Hemmje, Matthias (2016). Intuitive Knowledge Connectivity: Design and Prototyping of Cross-Platform Knowledge Networks. In Franz Lehner, Nora Fteimi (Hrsg.), Knowledge Science, Engineering and Management (S. 337-348). Cham, Switzerland: Springer International Publishing.

Kaufmann, Michael & Portmann, Edy (2015). Biomimetics in design-oriented information systems research. In Brian Donnellan, Rob Gleasure, Markus Helfert, Jim Kinneally, Marcus Rothenberger, Monica Chiarini Tremblay, Debra VanderMeer, Robert Winter (Hrsg.), At the Vanguard of Design Science: First Impressions and Early Findings from Ongoing Research Research-in-Progress Papers and Poster Presentations from the 10th International Conference, DESRIST 2015. Dublin, Ireland, 20-22 May. (S. 53-61). Cork: Lettertec Irl. Ltd.

Kaufmann, Michael; Portmann, Edy & Hinkelmann, Knut (2014). Combining Bottom-up and Top-down Generation of Interactive Knowledge Maps for Enterprise Search. In Robert Buchmann, Claudiu Vasile Kifor, Jian Yu (Hrsg.), Knowledge Science, Engineering and Management: Proceedings of the 7th International Conference, KSEM 2014 (S. 186-197). Cham Heidelberg New York Dordrecht London: Springer.

Kaufmann, Michael; Portmann, Edy & Fathi, Madjid (2013). A concept of semantics extraction from web data by induction of fuzzy ontologies. Proceedings of the 2013 IEEE International Conference on Electro/Information Technology (EIT) (S. 1-6). New York, NY: IEEE.

Portmann, Edy; Kaufmann, Michael & Graf, Cédric (2012). A distributed, semiotic-inductive, and human-oriented approach to web-scale knowledge retrieval. Proceedings of the 2012 international workshop on Web-scale knowledge representation, retrieval and reasoning (S. 1-8). New York, NY: ACM.

Kaufmann, Michael & Graf, Cédric (2012). Fuzzy Target Groups in Analytic Customer Relationship Management. In Meier, Andreas; Donzé, Laurent (Hrsg.), Fuzzy Methods for Customer Relationship Management and Marketing: Applications and Classifications. (S. 168-192). Hershey, PA: IGI Global, Business Science Reference.

Kaufmann, Michael (2009). An Inductive Approach to Fuzzy Marketing Analytics. Proceedings of the IASTED International Conference Artificial Intelligence and Soft Computing (ASC 2009) (S. 107-112). Calgary, CA: ACTA Press.

Kaufmann, Michael (2009). An inductive fuzzy classification approach applied to individual marketing. Annual Meeting of the North American Fuzzy Information Processing Society (S. 1-6). New York, NY: IEEE.

Zumstein, Darius & Kaufmann, Michael (2009). A Fuzzy Web Analytics Model for Web Mining. Proceedings of the IADIS Multi Conference on Computer Science and Information Systems (MCCSIS 2009) on Data Mining (S. 59-66). Lisbon, Portugal: IADIS Press.

Kaufmann, Michael (2016). Towards a Reference Model for Big Data Management (Forschungsbericht). Fakultät für Mathematik und Informatik, FernUniversität in Hagen, Hagen.

Drobnjak, Aleksandar; Kaufmann, Michael; Hugi, Patrik; Meier, Andreas; Schütze, Roland & Wehrle, Marcel (2011). Führungsinformationssysteme unter Nutzung der unscharfen Logik – Fallbeispiel coop@home (Bericht). Information Systems Research Group, Department of Informatics, University of Fribourg,

Kaufmann, Michael & Meier, Andreas (2008). An Inductive Fuzzy Classification Approach Applied to Individual Marketing (Bericht). Information Systems Research Group, Department of Informatics, University of Fribourg,

Eiholzer, Matthias & Kaufmann, Michael (2019). Method Engineering for Automatic Tagging with Inductive Fuzzy Classification (nicht veröffentlichte Master-/Lizentiats-/Diplomarbeit). Hochschule Luzern – Informatik, Rotkreuz, Switzerland.

Kaufmann, Michael (2012). Inductive Fuzzy Classification in Marketing Analytics. Dissertation, University of Fribourg, Switzerland.

Kaufmann, Michael (2005). Application of Fuzzy Classification to a Data Warehouse in E-Health (nicht veröffentlichte Master-/Lizentiats-/Diplomarbeit). University of Fribourg, Switzerland.

Kaufmann, Michael (2004). Reinforcement learning in autonomous robots (nicht veröffentlichte Bachelorarbeit). University of Fribourg, Switzerland.

Kaufmann, Michael (11.12.2017). Toward granular knowledge analytics for data intelligence: Extracting granular entity-relationship graphs for knowledge profiling. 2017 IEEE International Conference on Big Data (Big Data), Boston, MA.

Kaufmann, Michael (20.05.2015). Biomimetics in design-oriented information systems research. Tenth International Conference on Design Science Research in Information Systems and Technology DESRIST 2015, Dublin, Ireland.

Kaufmann, Michael (16.10.2014). Combining Bottom-up and Top-down Generation of Interactive Knowledge Maps for Enterprise Search. The 7th International Conference on Knowledge Science, Engineering and Management KSEM 2014, Sibiu, Romania.

Portmann, Edy & Kaufmann, Michael (29.10.2012). A Distributed, Semiotic-Inductive, and Human-Oriented Approach to Web-Scale Knowledge Retrieval. Web-KR '12 Proceedings of the 2012 international workshop on Web-scale knowledge representation, retrieval and reasoning, Maui, Hawaii, USA.

Kaufmann, Michael (07.09.2009). An Inductive Approach to Fuzzy Marketing Analytics. The IASTED International Conference Artificial Intelligence and Soft Computing (ASC 2009), Palma, Spain.