---
_id: '27381'
abstract:
- lang: eng
  text: Graph neural networks (GNNs) have been successfully applied in many structured
    data domains, with applications ranging from molecular property prediction to
    the analysis of social networks. Motivated by the broad applicability of GNNs,
    we propose the family of so-called RankGNNs, a combination of neural Learning
    to Rank (LtR) methods and GNNs. RankGNNs are trained with a set of pair-wise preferences
    between graphs, suggesting that one of them is preferred over the other. One practical
    application of this problem is drug screening, where an expert wants to find the
    most promising molecules in a large collection of drug candidates. We empirically
    demonstrate that our proposed pair-wise RankGNN approach either significantly
    outperforms or at least matches the ranking performance of the naive point-wise
    baseline approach, in which the LtR problem is solved via GNN-based graph regression.
author:
- first_name: Clemens
  full_name: Damke, Clemens
  id: '48192'
  last_name: Damke
  orcid: 0000-0002-0455-0048
- first_name: Eyke
  full_name: Hüllermeier, Eyke
  id: '48129'
  last_name: Hüllermeier
citation:
  ama: 'Damke C, Hüllermeier E. Ranking Structured Objects with Graph Neural Networks.
    In: Soares C, Torgo L, eds. <i>Proceedings of The 24th International Conference
    on Discovery Science (DS 2021)</i>. Vol 12986. Lecture Notes in Computer Science.
    Springer; 2021:166-180. doi:<a href="https://doi.org/10.1007/978-3-030-88942-5">10.1007/978-3-030-88942-5</a>'
  apa: Damke, C., &#38; Hüllermeier, E. (2021). Ranking Structured Objects with Graph
    Neural Networks. In C. Soares &#38; L. Torgo (Eds.), <i>Proceedings of The 24th
    International Conference on Discovery Science (DS 2021)</i> (Vol. 12986, pp. 166–180).
    Springer. <a href="https://doi.org/10.1007/978-3-030-88942-5">https://doi.org/10.1007/978-3-030-88942-5</a>
  bibtex: '@inproceedings{Damke_Hüllermeier_2021, series={Lecture Notes in Computer
    Science}, title={Ranking Structured Objects with Graph Neural Networks}, volume={12986},
    DOI={<a href="https://doi.org/10.1007/978-3-030-88942-5">10.1007/978-3-030-88942-5</a>},
    booktitle={Proceedings of The 24th International Conference on Discovery Science
    (DS 2021)}, publisher={Springer}, author={Damke, Clemens and Hüllermeier, Eyke},
    editor={Soares, Carlos and Torgo, Luis}, year={2021}, pages={166–180}, collection={Lecture
    Notes in Computer Science} }'
  chicago: Damke, Clemens, and Eyke Hüllermeier. “Ranking Structured Objects with
    Graph Neural Networks.” In <i>Proceedings of The 24th International Conference
    on Discovery Science (DS 2021)</i>, edited by Carlos Soares and Luis Torgo, 12986:166–80.
    Lecture Notes in Computer Science. Springer, 2021. <a href="https://doi.org/10.1007/978-3-030-88942-5">https://doi.org/10.1007/978-3-030-88942-5</a>.
  ieee: 'C. Damke and E. Hüllermeier, “Ranking Structured Objects with Graph Neural
    Networks,” in <i>Proceedings of The 24th International Conference on Discovery
    Science (DS 2021)</i>, Halifax, Canada, 2021, vol. 12986, pp. 166–180, doi: <a
    href="https://doi.org/10.1007/978-3-030-88942-5">10.1007/978-3-030-88942-5</a>.'
  mla: Damke, Clemens, and Eyke Hüllermeier. “Ranking Structured Objects with Graph
    Neural Networks.” <i>Proceedings of The 24th International Conference on Discovery
    Science (DS 2021)</i>, edited by Carlos Soares and Luis Torgo, vol. 12986, Springer,
    2021, pp. 166–80, doi:<a href="https://doi.org/10.1007/978-3-030-88942-5">10.1007/978-3-030-88942-5</a>.
  short: 'C. Damke, E. Hüllermeier, in: C. Soares, L. Torgo (Eds.), Proceedings of
    The 24th International Conference on Discovery Science (DS 2021), Springer, 2021,
    pp. 166–180.'
conference:
  end_date: 2021-10-13
  location: Halifax, Canada
  name: 24th International Conference on Discovery Science
  start_date: 2021-10-11
date_created: 2021-11-11T14:15:18Z
date_updated: 2022-04-11T22:08:12Z
department:
- _id: '355'
doi: 10.1007/978-3-030-88942-5
editor:
- first_name: Carlos
  full_name: Soares, Carlos
  last_name: Soares
- first_name: Luis
  full_name: Torgo, Luis
  last_name: Torgo
external_id:
  arxiv:
  - '2104.08869'
intvolume: '     12986'
keyword:
- Graph-structured data
- Graph neural networks
- Preference learning
- Learning to rank
language:
- iso: eng
page: 166-180
publication: Proceedings of The 24th International Conference on Discovery Science
  (DS 2021)
publication_identifier:
  isbn:
  - '9783030889418'
  - '9783030889425'
  issn:
  - 0302-9743
  - 1611-3349
publication_status: published
publisher: Springer
quality_controlled: '1'
series_title: Lecture Notes in Computer Science
status: public
title: Ranking Structured Objects with Graph Neural Networks
type: conference
user_id: '48192'
volume: 12986
year: '2021'
...