Skip to main content

User account menu

  • Log in
DBS-Logo

Database Group Leipzig

within the department of computer science

ScaDS-Logo Logo of the University of Leipzig

Main navigation

  • Home
  • Study
    • Exams
      • Hinweise zu Klausuren
    • Courses
      • Current
    • Modules
    • LOTS-Training
    • Abschlussarbeiten
    • Masterstudiengang Data Science
    • Oberseminare
    • Problemseminare
    • Top-Studierende
  • Research
    • Projects
      • Benchmark datasets for entity resolution
      • FAMER
      • HyGraph
      • Privacy-Preserving Record Linkage
      • GRADOOP
    • Publications
    • Prototypes
    • Annual reports
    • Cooperations
    • Graduations
    • Colloquia
    • Conferences
  • Team
    • Erhard Rahm
    • Member
    • Former employees
    • Associated members
    • Gallery

Preserving Recomputability of Results from Big Data Transformation Workflows

Breadcrumb

  • Home
  • Research
  • Publications
  • Preserving Recomputability of Results from Big Data Transformation Workflows

Kricke, M. ; Grimmer, M. ; Schmeißer, M.

Preserving Recomputability of Results from Big Data Transformation Workflows

Workshop Proceedings BTW, Lecture Notes in Informatics(LNI), GI 2017

2017 / 03

Paper

Abstract

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: Automated Configuration of Schema Matching Tools: A Reinforcement Learning Approach
  • 2025 / 3: Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning

Footer menu

  • Directions
  • Contact
  • Impressum