Lehr- und Forschungseinheit für Datenbanksysteme

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Ludwig Zellner

Research Assistant


Ludwig-Maximilians-Universität München
Lehrstuhl für Datenbanksysteme und Data Mining
Oettingenstraße 67
80538 München

Room: F104
Phone: +49-89-2180-9321
Fax: +49-89-2180-9192

Research Interests:

  • Process Mining
  • Sequential Rule Mining
  • Recommender Systems
  • Anomaly Detection
  • Concept Drift Detection


Supervised Theses:

  • Examining Filter Bubbles over Time: A Sequential Rule Mining Approach
  • Comparing Recommender Systems on a Successive-Item-Recommendation Task
  • Dynamic Ranking of Sequential Rules Based on Discrete Gaps
  • Dynamic Ranking of Sequential Rules Based on Continuous Gaps
  • Analysing Parameter Impact and Quality Measures for Designated Rule Mining Algorithms
  • On the Optimization of Partially-Ordered Sequential Rule Mining
  • Utilising Sequential Rule Mining for Conformance Checking
  • Comparing Types of Sequential Rule Mining for Recommendation Purposes
  • Using Graph Similarity For Concept Drift Detection
  • Discovering Frequent Subtraces with Gaps on Unstructured Processes
  • k-Lines Clustering: Extending k-Means to Linearly Correlated Data
  • Coalition-Based Ranking on Process Graphs

Possible Phases of a Thesis:





Academic Service:

Reviewing for DSAA (DSAA'19), 2 x DAMI (DAMI'20), EDBT (EDBT'23), BTW (BTW'23), 2 x Data & Knowledge Engineering Journal (DATAK'23), ECAI (ECAI'23), 2 x ICDE (ICDE'24)