Experimental data for the paper "quantifying domain-application knowledge mismatch in ontology-guided machine learning"

Abstract: These are experimental data for the paper: Pawel Bielski, Lena Witterauf, Sönke Jendral, Ralf Mikut, Jakob Bach. 2024. Quantifying Domain-Application Knowledge Mismatch in Ontology-Guided Machine Learning, 16th International Conference on Knowledge Engineering and Ontology Development (KEOD), Porto, Portugal. The data consist of the results from the experiments and the corresponding code to create plots used in the paper. TechnicalRemarks: ## Folder Structure

  • Use Case 1 Computer Vision: contains jupyter notebook files to compute refinement scores for the three image classification dataset, the pickle files with the computed refinement scores, and the file to generate plots used in the paper.
  • Use Case 2 Healthcare: contains two subfolders
  • experiments_code contains the code used to reproduce the experiments on the MIMIC-III Dataset.
  • experimental_results_code contains the jupyter notebook files to compute the refinement scores for the next sequence prediction and risk prediction tasks, the pickle files with the computed refinement scores, and the file to generate plots used in the paper.

Cite this as

Bielski, Pawel, Witterauf, Lena (2024). Dataset: Experimental data for the paper "quantifying domain-application knowledge mismatch in ontology-guided machine learning". https://doi.org/10.35097/zv8zqgqd6ezm02vk

DOI retrieved: 2024

Additional Info

Field Value
Imported on November 28, 2024
Last update November 28, 2024
License CC BY 4.0 Attribution
Source https://doi.org/10.35097/zv8zqgqd6ezm02vk
Author Bielski, Pawel
Given Name Pawel
Family Name Bielski
More Authors
Witterauf, Lena
Source Creation 2024
Publishers
Karlsruhe Institute of Technology
Production Year 2024
Publication Year 2024
Subject Areas
Name: Other
Additional: Allgemeines, Hochschulwesen, Wissenschaft und Forschung

Related Identifiers
Identifier: https://publikationen.bibliothek.kit.edu/1000174629
Type: URL
Relation: IsIdenticalTo