---
_id: '31806'
abstract:
- lang: eng
  text: The creation of an RDF knowledge graph for a particular application commonly
    involves a pipeline of tools that transform a set ofinput data sources into an
    RDF knowledge graph in a process called dataset augmentation. The components of
    such augmentation pipelines often require extensive configuration to lead to satisfactory
    results. Thus, non-experts are often unable to use them. Wepresent an efficient
    supervised algorithm based on genetic programming for learning knowledge graph
    augmentation pipelines of arbitrary length. Our approach uses multi-expression
    learning to learn augmentation pipelines able to achieve a high F-measure on the
    training data. Our evaluation suggests that our approach can efficiently learn
    a larger class of RDF dataset augmentation tasks than the state of the art while
    using only a single training example. Even on the most complex augmentation problem
    we posed, our approach consistently achieves an average F1-measure of 99% in under
    500 iterations with an average runtime of 16 seconds
author:
- first_name: Kevin
  full_name: Dreßler, Kevin
  id: '78256'
  last_name: Dreßler
- first_name: Mohamed
  full_name: Sherif, Mohamed
  id: '67234'
  last_name: Sherif
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  id: '65716'
  last_name: Ngonga Ngomo
citation:
  ama: 'Dreßler K, Sherif M, Ngonga Ngomo A-C. ADAGIO - Automated Data Augmentation
    of Knowledge Graphs Using Multi-expression Learning. In: <i>Proceedings of the
    33rd ACM Conference on Hypertext and Hypermedia</i>. ; 2022. doi:<a href="https://doi.org/10.1145/3511095.3531287">10.1145/3511095.3531287</a>'
  apa: 'Dreßler, K., Sherif, M., &#38; Ngonga Ngomo, A.-C. (2022). ADAGIO - Automated
    Data Augmentation of Knowledge Graphs Using Multi-expression Learning. <i>Proceedings
    of the 33rd ACM Conference on Hypertext and Hypermedia</i>. HT ’22: 33rd ACM Conference
    on Hypertext and Social Media, Barcelona (Spain). <a href="https://doi.org/10.1145/3511095.3531287">https://doi.org/10.1145/3511095.3531287</a>'
  bibtex: '@inproceedings{Dreßler_Sherif_Ngonga Ngomo_2022, title={ADAGIO - Automated
    Data Augmentation of Knowledge Graphs Using Multi-expression Learning}, DOI={<a
    href="https://doi.org/10.1145/3511095.3531287">10.1145/3511095.3531287</a>}, booktitle={Proceedings
    of the 33rd ACM Conference on Hypertext and Hypermedia}, author={Dreßler, Kevin
    and Sherif, Mohamed and Ngonga Ngomo, Axel-Cyrille}, year={2022} }'
  chicago: Dreßler, Kevin, Mohamed Sherif, and Axel-Cyrille Ngonga Ngomo. “ADAGIO
    - Automated Data Augmentation of Knowledge Graphs Using Multi-Expression Learning.”
    In <i>Proceedings of the 33rd ACM Conference on Hypertext and Hypermedia</i>,
    2022. <a href="https://doi.org/10.1145/3511095.3531287">https://doi.org/10.1145/3511095.3531287</a>.
  ieee: 'K. Dreßler, M. Sherif, and A.-C. Ngonga Ngomo, “ADAGIO - Automated Data Augmentation
    of Knowledge Graphs Using Multi-expression Learning,” presented at the HT ’22:
    33rd ACM Conference on Hypertext and Social Media, Barcelona (Spain), 2022, doi:
    <a href="https://doi.org/10.1145/3511095.3531287">10.1145/3511095.3531287</a>.'
  mla: Dreßler, Kevin, et al. “ADAGIO - Automated Data Augmentation of Knowledge Graphs
    Using Multi-Expression Learning.” <i>Proceedings of the 33rd ACM Conference on
    Hypertext and Hypermedia</i>, 2022, doi:<a href="https://doi.org/10.1145/3511095.3531287">10.1145/3511095.3531287</a>.
  short: 'K. Dreßler, M. Sherif, A.-C. Ngonga Ngomo, in: Proceedings of the 33rd ACM
    Conference on Hypertext and Hypermedia, 2022.'
conference:
  end_date: 2022-07-01
  location: Barcelona (Spain)
  name: 'HT ’22: 33rd ACM Conference on Hypertext and Social Media'
  start_date: 2022-06-28
date_created: 2022-06-08T08:47:33Z
date_updated: 2022-11-18T10:11:38Z
ddc:
- '000'
department:
- _id: '34'
doi: 10.1145/3511095.3531287
keyword:
- 2022 RAKI SFB901 deer dice kevin knowgraphs limes ngonga sherif simba
language:
- iso: eng
project:
- _id: '1'
  name: 'SFB 901: SFB 901'
- _id: '3'
  name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '10'
  name: 'SFB 901 - B2: SFB 901 - Subproject B2'
publication: Proceedings of the 33rd ACM Conference on Hypertext and Hypermedia
status: public
title: ADAGIO - Automated Data Augmentation of Knowledge Graphs Using Multi-expression
  Learning
type: conference
user_id: '477'
year: '2022'
...