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Müller, Robert

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Publications (21)

Dateien Cover Beschreibung Jahr
Graph-based Data Integration and Business Intelligence with BIIIG
Petermann, A. ; Junghanns, M. ; Müller, R. ; Rahm, E.
Proc. VLDB Conf., 2014 (Demo paper)
2014 / 9
FoodBroker - Generating Synthetic Datasets for Graph-Based Business Analytics
Petermann, A. ; Junghanns, M. ; Müller, R. ; Rahm, E.
5th Workshop on Big Data Benchmarking (WBDB 2014), LNCS 8991, 2015
2014 / 8
BIIIG : Enabling Business Intelligence with Integrated Instance Graphs
Petermann, A. ; Junghanns, M. ; Müller, R. ; Rahm, E.
5th International Workshop on Graph Data Management (GDM 2014)
2014 / 3
AdaptFlow: Protocol-based Medical Treatment Using Adaptive Workflows
Greiner, U. ; Müller, R. ; Rahm, E. ; Ramsch, J. ; Heller, B. ; Löffler, M.
Methods of Information in Medicine
2005
AGENTWORK: A Workflow-System Supporting Rule-Based Workflow Adaptation.
Müller, R. ; Greiner, U. ; Rahm, E.
Data and Knowledge Engineering, Elsevier, 2004
2004
Adaptive Guideline-based Treatment Workflows with AdaptFlow.
Greiner, U. ; Ramsch, J. ; Heller, B. ; Löffler, M. ; Müller, R. ; Rahm, E.
Proc. Symposium on Computerized Guidelines and Protocols (CGP 2004), Prague, IOS Press, April 2004.
2004
Event-Oriented Dynamic Adaptation of Workflows: Model, Architecture and Implementation
Müller, R.
Dissertation, Univ. Leipzig
2002
Evaluierung von Data Warehouse-Werkzeugen.
Do, H. ; Stöhr, T. ; Rahm, E. ; Müller, R. ; Dern, G.
Proc. Data Warehousing (DW) 2000, Friedrichshafen, Nov. 2000
2000
Dealing with Logical Failures for Collaborating Workflows.
Müller, R. ; Rahm, E.
In Etzion, O.; Scheuermann, P. (Eds.): Proceedings CoopIS 2000, Eilat, Israel, September 6-8 LNCS 1901). Springer, Berlin, 2000: 210-223.
2000
Rule-Based Dynamic Modification of Workflows in a Medical Domain,
Müller, R. ; Rahm, E.
Proceedings of BTW99 (Datenbanksysteme für Büro, Technik und Wissenschaft) , Freiburg im Breisgau, 1.-3.März 1999. Springer, Berlin 1999: 429-448
1999

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Recent publications

  • 2025 / 8: Slice it up: Unmasking User Identities in Smartwatch Health Data
  • 2025 / 6: SecUREmatch: Integrating Clerical Review in Privacy-Preserving Record Linkage
  • 2025 / 5: Federated Learning With Individualized Privacy Through Client Sampling
  • 2025 / 3: Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning
  • 2025 / 3: Automated Configuration of Schema Matching Tools: A Reinforcement Learning Approach

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