---
_id: '63918'
abstract:
- lang: eng
text: Many real-world datasets, such as citation networks, social networks, and
molecular structures, are naturally represented as heterogeneous graphs, where
nodes belong to different types and have additional features. For example, in
a citation network, nodes representing "Paper" or "Author" may include attributes
like keywords or affiliations. A critical machine learning task on these graphs
is node classification, which is useful for applications such as fake news detection,
corporate risk assessment, and molecular property prediction. Although Heterogeneous
Graph Neural Networks (HGNNs) perform well in these contexts, their predictions
remain opaque. Existing post-hoc explanation methods lack support for actual node
features beyond one-hot encoding of node type and often fail to generate realistic,
faithful explanations. To address these gaps, we propose DiGNNExplainer, a model-level
explanation approach that synthesizes heterogeneous graphs with realistic node
features via discrete denoising diffusion. In particular, we generate realistic
discrete features (e.g., bag-of-words features) using diffusion models within
a discrete space, whereas previous approaches are limited to continuous spaces.
We evaluate our approach on multiple datasets and show that DiGNNExplainer produces
explanations that are realistic and faithful to the model's decision-making, outperforming
state-of-the-art methods.
author:
- first_name: Pallabee
full_name: Das, Pallabee
last_name: Das
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
citation:
ama: 'Das P, Heindorf S. Discrete Diffusion-Based Model-Level Explanation of Heterogeneous
GNNs with Node Features. In: Proceedings of the ACM Web Conference 2026 (WWW
’26). ACM; 2026.'
apa: Das, P., & Heindorf, S. (2026). Discrete Diffusion-Based Model-Level Explanation
of Heterogeneous GNNs with Node Features. Proceedings of the ACM Web Conference
2026 (WWW ’26). The Web Conference, Dubai, United Arab Emirates.
bibtex: '@inproceedings{Das_Heindorf_2026, title={Discrete Diffusion-Based Model-Level
Explanation of Heterogeneous GNNs with Node Features}, booktitle={Proceedings
of the ACM Web Conference 2026 (WWW ’26)}, publisher={ACM}, author={Das, Pallabee
and Heindorf, Stefan}, year={2026} }'
chicago: Das, Pallabee, and Stefan Heindorf. “Discrete Diffusion-Based Model-Level
Explanation of Heterogeneous GNNs with Node Features.” In Proceedings of the
ACM Web Conference 2026 (WWW ’26). ACM, 2026.
ieee: P. Das and S. Heindorf, “Discrete Diffusion-Based Model-Level Explanation
of Heterogeneous GNNs with Node Features,” presented at the The Web Conference,
Dubai, United Arab Emirates, 2026.
mla: Das, Pallabee, and Stefan Heindorf. “Discrete Diffusion-Based Model-Level Explanation
of Heterogeneous GNNs with Node Features.” Proceedings of the ACM Web Conference
2026 (WWW ’26), ACM, 2026.
short: 'P. Das, S. Heindorf, in: Proceedings of the ACM Web Conference 2026 (WWW
’26), ACM, 2026.'
conference:
end_date: 2026-04-17
location: Dubai, United Arab Emirates
name: The Web Conference
start_date: 2026-04-13
date_created: 2026-02-06T18:44:34Z
date_updated: 2026-02-06T18:47:38Z
department:
- _id: '760'
external_id:
arxiv:
- '2508.08458'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/pdf/2508.08458
oa: '1'
publication: Proceedings of the ACM Web Conference 2026 (WWW ’26)
publisher: ACM
status: public
title: Discrete Diffusion-Based Model-Level Explanation of Heterogeneous GNNs with
Node Features
type: conference
user_id: '11871'
year: '2026'
...
---
_id: '54450'
abstract:
- lang: eng
text: In the last decade, there has been increasing interest in allowing users to
understand how the predictions of machine-learned models come about, thus increasing
transparency and empowering users to understand and potentially contest those
decisions.Dialogue-based approaches, in contrast to traditional one-shot eXplainable
Artificial Intelligence (XAI) methods, facilitate interactive, in-depth exploration
through multi-turn dialogues, simulating expert conversations. This paper reviews
the current state of dialogue-based XAI, presenting a systematic review of 1,339
publications, narrowed down to 14 based on inclusion criteria. We explore theoretical
foundations of the systems, propose key dimensions along which different solutions
to dialogue-based XAI differ, and identify key use cases, target audiences, system
components, and the types of supported queries and responses. Furthermore, we
investigate the current paradigms by which systems are evaluated and highlight
their key limitations. Key findings include identifying the main use cases, objectives,
and audiences targeted by dialogue-based XAI methods, and summarize the main types
of questions and information needs. Beyond discussing avenues for future work,
we present a meta-architecture for these systems from existing literature and
outlined prevalent theoretical frameworks.
article_number: '81'
author:
- first_name: Dimitry
full_name: Mindlin, Dimitry
last_name: Mindlin
- first_name: Fabian
full_name: Beer, Fabian
last_name: Beer
- first_name: Leonie Nora
full_name: Sieger, Leonie Nora
id: '93402'
last_name: Sieger
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Philipp
full_name: Cimiano, Philipp
last_name: Cimiano
- first_name: Elena
full_name: Esposito, Elena
last_name: Esposito
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Mindlin D, Beer F, Sieger LN, et al. Beyond One-Shot Explanations: A Systematic
Literature Review of Dialogue-Based XAI Approaches. Artificial Intelligence
Review. 2025;58(3). doi:10.1007/s10462-024-11007-7'
apa: 'Mindlin, D., Beer, F., Sieger, L. N., Heindorf, S., Cimiano, P., Esposito,
E., & Ngonga Ngomo, A.-C. (2025). Beyond One-Shot Explanations: A Systematic
Literature Review of Dialogue-Based XAI Approaches. Artificial Intelligence
Review, 58(3), Article 81. https://doi.org/10.1007/s10462-024-11007-7'
bibtex: '@article{Mindlin_Beer_Sieger_Heindorf_Cimiano_Esposito_Ngonga Ngomo_2025,
title={Beyond One-Shot Explanations: A Systematic Literature Review of Dialogue-Based
XAI Approaches}, volume={58}, DOI={10.1007/s10462-024-11007-7},
number={381}, journal={Artificial Intelligence Review}, publisher={Springer},
author={Mindlin, Dimitry and Beer, Fabian and Sieger, Leonie Nora and Heindorf,
Stefan and Cimiano, Philipp and Esposito, Elena and Ngonga Ngomo, Axel-Cyrille},
year={2025} }'
chicago: 'Mindlin, Dimitry, Fabian Beer, Leonie Nora Sieger, Stefan Heindorf, Philipp
Cimiano, Elena Esposito, and Axel-Cyrille Ngonga Ngomo. “Beyond One-Shot Explanations:
A Systematic Literature Review of Dialogue-Based XAI Approaches.” Artificial
Intelligence Review 58, no. 3 (2025). https://doi.org/10.1007/s10462-024-11007-7.'
ieee: 'D. Mindlin et al., “Beyond One-Shot Explanations: A Systematic Literature
Review of Dialogue-Based XAI Approaches,” Artificial Intelligence Review,
vol. 58, no. 3, Art. no. 81, 2025, doi: 10.1007/s10462-024-11007-7.'
mla: 'Mindlin, Dimitry, et al. “Beyond One-Shot Explanations: A Systematic Literature
Review of Dialogue-Based XAI Approaches.” Artificial Intelligence Review,
vol. 58, no. 3, 81, Springer, 2025, doi:10.1007/s10462-024-11007-7.'
short: D. Mindlin, F. Beer, L.N. Sieger, S. Heindorf, P. Cimiano, E. Esposito, A.-C.
Ngonga Ngomo, Artificial Intelligence Review 58 (2025).
date_created: 2024-05-26T18:55:58Z
date_updated: 2025-01-24T20:09:20Z
department:
- _id: '760'
- _id: '574'
doi: 10.1007/s10462-024-11007-7
intvolume: ' 58'
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://link.springer.com/article/10.1007/s10462-024-11007-7
oa: '1'
publication: Artificial Intelligence Review
publication_status: published
publisher: Springer
status: public
title: 'Beyond One-Shot Explanations: A Systematic Literature Review of Dialogue-Based
XAI Approaches'
type: journal_article
user_id: '11871'
volume: 58
year: '2025'
...
---
_id: '64206'
author:
- first_name: Sebastian
full_name: Groß, Sebastian
last_name: Groß
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Philipp
full_name: Terhörst, Philipp
id: '97123'
last_name: Terhörst
citation:
ama: Groß S, Heindorf S, Terhörst P. A Responsible Face Recognition Approach for
Small and Mid-Scale Systems Through Personalized Neural Networks. CoRR.
2025;abs/2505.19920. doi:10.48550/ARXIV.2505.19920
apa: Groß, S., Heindorf, S., & Terhörst, P. (2025). A Responsible Face Recognition
Approach for Small and Mid-Scale Systems Through Personalized Neural Networks.
CoRR, abs/2505.19920. https://doi.org/10.48550/ARXIV.2505.19920
bibtex: '@article{Groß_Heindorf_Terhörst_2025, title={A Responsible Face Recognition
Approach for Small and Mid-Scale Systems Through Personalized Neural Networks},
volume={abs/2505.19920}, DOI={10.48550/ARXIV.2505.19920},
journal={CoRR}, author={Groß, Sebastian and Heindorf, Stefan and Terhörst, Philipp},
year={2025} }'
chicago: Groß, Sebastian, Stefan Heindorf, and Philipp Terhörst. “A Responsible
Face Recognition Approach for Small and Mid-Scale Systems Through Personalized
Neural Networks.” CoRR abs/2505.19920 (2025). https://doi.org/10.48550/ARXIV.2505.19920.
ieee: 'S. Groß, S. Heindorf, and P. Terhörst, “A Responsible Face Recognition Approach
for Small and Mid-Scale Systems Through Personalized Neural Networks,” CoRR,
vol. abs/2505.19920, 2025, doi: 10.48550/ARXIV.2505.19920.'
mla: Groß, Sebastian, et al. “A Responsible Face Recognition Approach for Small
and Mid-Scale Systems Through Personalized Neural Networks.” CoRR, vol.
abs/2505.19920, 2025, doi:10.48550/ARXIV.2505.19920.
short: S. Groß, S. Heindorf, P. Terhörst, CoRR abs/2505.19920 (2025).
date_created: 2026-02-18T09:43:56Z
date_updated: 2026-02-19T07:52:13Z
doi: 10.48550/ARXIV.2505.19920
language:
- iso: eng
publication: CoRR
status: public
title: A Responsible Face Recognition Approach for Small and Mid-Scale Systems Through
Personalized Neural Networks
type: journal_article
user_id: '97123'
volume: abs/2505.19920
year: '2025'
...
---
_id: '62707'
author:
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Daniel
full_name: Neib, Daniel
last_name: Neib
citation:
ama: 'Heindorf S, Neib D. Assessing Natural Language Explanations of Relational
Graph Neural Networks. In: Proceedings of the 34th ACM International Conference
on Information and Knowledge Management. ACM; 2025. doi:10.1145/3746252.3760918'
apa: Heindorf, S., & Neib, D. (2025). Assessing Natural Language Explanations
of Relational Graph Neural Networks. Proceedings of the 34th ACM International
Conference on Information and Knowledge Management. https://doi.org/10.1145/3746252.3760918
bibtex: '@inproceedings{Heindorf_Neib_2025, title={Assessing Natural Language Explanations
of Relational Graph Neural Networks}, DOI={10.1145/3746252.3760918},
booktitle={Proceedings of the 34th ACM International Conference on Information
and Knowledge Management}, publisher={ACM}, author={Heindorf, Stefan and Neib,
Daniel}, year={2025} }'
chicago: Heindorf, Stefan, and Daniel Neib. “Assessing Natural Language Explanations
of Relational Graph Neural Networks.” In Proceedings of the 34th ACM International
Conference on Information and Knowledge Management. ACM, 2025. https://doi.org/10.1145/3746252.3760918.
ieee: 'S. Heindorf and D. Neib, “Assessing Natural Language Explanations of Relational
Graph Neural Networks,” 2025, doi: 10.1145/3746252.3760918.'
mla: Heindorf, Stefan, and Daniel Neib. “Assessing Natural Language Explanations
of Relational Graph Neural Networks.” Proceedings of the 34th ACM International
Conference on Information and Knowledge Management, ACM, 2025, doi:10.1145/3746252.3760918.
short: 'S. Heindorf, D. Neib, in: Proceedings of the 34th ACM International Conference
on Information and Knowledge Management, ACM, 2025.'
date_created: 2025-11-28T15:36:11Z
date_updated: 2025-11-28T15:36:57Z
department:
- _id: '760'
doi: 10.1145/3746252.3760918
language:
- iso: eng
publication: Proceedings of the 34th ACM International Conference on Information and
Knowledge Management
publication_status: published
publisher: ACM
status: public
title: Assessing Natural Language Explanations of Relational Graph Neural Networks
type: conference
user_id: '11871'
year: '2025'
...
---
_id: '54449'
author:
- first_name: N'Dah Jean
full_name: KOUAGOU, N'Dah Jean
id: '87189'
last_name: KOUAGOU
- first_name: Caglar
full_name: Demir, Caglar
id: '43817'
last_name: Demir
- first_name: Hamada Mohamed Abdelsamee
full_name: Zahera, Hamada Mohamed Abdelsamee
id: '72768'
last_name: Zahera
orcid: 0000-0003-0215-1278
- first_name: Adrian
full_name: Wilke, Adrian
id: '9101'
last_name: Wilke
orcid: 0000-0002-6575-807X
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Jiayi
full_name: Li, Jiayi
last_name: Li
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'KOUAGOU NJ, Demir C, Zahera HMA, et al. Universal Knowledge Graph Embeddings.
In: Companion Proceedings of the ACM on Web Conference 2024. ACM; 2024.
doi:10.1145/3589335.3651978'
apa: KOUAGOU, N. J., Demir, C., Zahera, H. M. A., Wilke, A., Heindorf, S., Li, J.,
& Ngonga Ngomo, A.-C. (2024). Universal Knowledge Graph Embeddings. Companion
Proceedings of the ACM on Web Conference 2024. Companion Proceedings of the
ACM on Web Conference 2024, Singapore. https://doi.org/10.1145/3589335.3651978
bibtex: '@inproceedings{KOUAGOU_Demir_Zahera_Wilke_Heindorf_Li_Ngonga Ngomo_2024,
title={Universal Knowledge Graph Embeddings}, DOI={10.1145/3589335.3651978},
booktitle={Companion Proceedings of the ACM on Web Conference 2024}, publisher={ACM},
author={KOUAGOU, N’Dah Jean and Demir, Caglar and Zahera, Hamada Mohamed Abdelsamee
and Wilke, Adrian and Heindorf, Stefan and Li, Jiayi and Ngonga Ngomo, Axel-Cyrille},
year={2024} }'
chicago: KOUAGOU, N’Dah Jean, Caglar Demir, Hamada Mohamed Abdelsamee Zahera, Adrian
Wilke, Stefan Heindorf, Jiayi Li, and Axel-Cyrille Ngonga Ngomo. “Universal Knowledge
Graph Embeddings.” In Companion Proceedings of the ACM on Web Conference 2024.
ACM, 2024. https://doi.org/10.1145/3589335.3651978.
ieee: 'N. J. KOUAGOU et al., “Universal Knowledge Graph Embeddings,” presented
at the Companion Proceedings of the ACM on Web Conference 2024, Singapore, 2024,
doi: 10.1145/3589335.3651978.'
mla: KOUAGOU, N’Dah Jean, et al. “Universal Knowledge Graph Embeddings.” Companion
Proceedings of the ACM on Web Conference 2024, ACM, 2024, doi:10.1145/3589335.3651978.
short: 'N.J. KOUAGOU, C. Demir, H.M.A. Zahera, A. Wilke, S. Heindorf, J. Li, A.-C.
Ngonga Ngomo, in: Companion Proceedings of the ACM on Web Conference 2024, ACM,
2024.'
conference:
end_date: 2024-05-17
location: Singapore
name: Companion Proceedings of the ACM on Web Conference 2024
start_date: 2024-05-13
date_created: 2024-05-26T18:52:47Z
date_updated: 2024-05-26T19:06:10Z
department:
- _id: '760'
- _id: '574'
doi: 10.1145/3589335.3651978
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://dl.acm.org/doi/abs/10.1145/3589335.3651978
oa: '1'
publication: Companion Proceedings of the ACM on Web Conference 2024
publication_status: published
publisher: ACM
status: public
title: Universal Knowledge Graph Embeddings
type: conference
user_id: '11871'
year: '2024'
...
---
_id: '54448'
abstract:
- lang: eng
text: "Graph Neural Networks (GNNs) are effective for node classification in\r\ngraph-structured
data, but they lack explainability, especially at the global\r\nlevel. Current
research mainly utilizes subgraphs of the input as local\r\nexplanations or generates
new graphs as global explanations. However, these\r\ngraph-based methods are limited
in their ability to explain classes with\r\nmultiple sufficient explanations.
To provide more expressive explanations, we\r\npropose utilizing class expressions
(CEs) from the field of description logic\r\n(DL). Our approach explains heterogeneous
graphs with different types of nodes\r\nusing CEs in the EL description logic.
To identify the best explanation among\r\nmultiple candidate explanations, we
employ and compare two different scoring\r\nfunctions: (1) For a given CE, we
construct multiple graphs, have the GNN make\r\na prediction for each graph, and
aggregate the predicted scores. (2) We score\r\nthe CE in terms of fidelity, i.e.,
we compare the predictions of the GNN to the\r\npredictions by the CE on a separate
validation set. Instead of subgraph-based\r\nexplanations, we offer CE-based explanations."
author:
- first_name: Dominik
full_name: Köhler, Dominik
last_name: Köhler
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
citation:
ama: Köhler D, Heindorf S. Utilizing Description Logics for Global Explanations
of Heterogeneous Graph Neural Networks. arXiv:240512654. Published online
2024.
apa: Köhler, D., & Heindorf, S. (2024). Utilizing Description Logics for Global
Explanations of Heterogeneous Graph Neural Networks. In arXiv:2405.12654.
bibtex: '@article{Köhler_Heindorf_2024, title={Utilizing Description Logics for
Global Explanations of Heterogeneous Graph Neural Networks}, journal={arXiv:2405.12654},
author={Köhler, Dominik and Heindorf, Stefan}, year={2024} }'
chicago: Köhler, Dominik, and Stefan Heindorf. “Utilizing Description Logics for
Global Explanations of Heterogeneous Graph Neural Networks.” ArXiv:2405.12654,
2024.
ieee: D. Köhler and S. Heindorf, “Utilizing Description Logics for Global Explanations
of Heterogeneous Graph Neural Networks,” arXiv:2405.12654. 2024.
mla: Köhler, Dominik, and Stefan Heindorf. “Utilizing Description Logics for Global
Explanations of Heterogeneous Graph Neural Networks.” ArXiv:2405.12654,
2024.
short: D. Köhler, S. Heindorf, ArXiv:2405.12654 (2024).
date_created: 2024-05-26T18:49:59Z
date_updated: 2024-05-26T19:04:55Z
department:
- _id: '760'
external_id:
arxiv:
- '2405.12654'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2405.12654
oa: '1'
publication: arXiv:2405.12654
status: public
title: Utilizing Description Logics for Global Explanations of Heterogeneous Graph
Neural Networks
type: preprint
user_id: '11871'
year: '2024'
...
---
_id: '52231'
author:
- first_name: Lukas
full_name: Blübaum, Lukas
last_name: Blübaum
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
citation:
ama: 'Blübaum L, Heindorf S. Causal Question Answering with Reinforcement Learning.
In: The World Wide Web Conference (WWW). ACM; :2204–2215. doi:10.1145/3589334.3645610'
apa: Blübaum, L., & Heindorf, S. (n.d.). Causal Question Answering with Reinforcement
Learning. The World Wide Web Conference (WWW), 2204–2215. https://doi.org/10.1145/3589334.3645610
bibtex: '@inproceedings{Blübaum_Heindorf, title={Causal Question Answering with
Reinforcement Learning}, DOI={10.1145/3589334.3645610},
booktitle={The World Wide Web Conference (WWW)}, publisher={ACM}, author={Blübaum,
Lukas and Heindorf, Stefan}, pages={2204–2215} }'
chicago: Blübaum, Lukas, and Stefan Heindorf. “Causal Question Answering with Reinforcement
Learning.” In The World Wide Web Conference (WWW), 2204–2215. ACM, n.d.
https://doi.org/10.1145/3589334.3645610.
ieee: 'L. Blübaum and S. Heindorf, “Causal Question Answering with Reinforcement
Learning,” in The World Wide Web Conference (WWW), Singapore, pp. 2204–2215,
doi: 10.1145/3589334.3645610.'
mla: Blübaum, Lukas, and Stefan Heindorf. “Causal Question Answering with Reinforcement
Learning.” The World Wide Web Conference (WWW), ACM, pp. 2204–2215, doi:10.1145/3589334.3645610.
short: 'L. Blübaum, S. Heindorf, in: The World Wide Web Conference (WWW), ACM, n.d.,
pp. 2204–2215.'
conference:
end_date: 2024-05-17
location: Singapore
name: The Web Conference
start_date: 2024-05-13
date_created: 2024-03-01T16:32:39Z
date_updated: 2024-05-26T19:01:34Z
department:
- _id: '760'
doi: 10.1145/3589334.3645610
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2311.02760
oa: '1'
page: 2204–2215
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: The World Wide Web Conference (WWW)
publication_status: accepted
publisher: ACM
status: public
title: Causal Question Answering with Reinforcement Learning
type: conference
user_id: '11871'
year: '2024'
...
---
_id: '56213'
author:
- first_name: Rupesh
full_name: Sapkota, Rupesh
id: '89326'
last_name: Sapkota
- first_name: Dominik
full_name: Köhler, Dominik
last_name: Köhler
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
citation:
ama: 'Sapkota R, Köhler D, Heindorf S. EDGE: Evaluation Framework for Logical vs.
Subgraph Explanations for Node Classifiers on Knowledge Graphs. In: Proceedings
of the 33rd ACM International Conference on Information and Knowledge Management
(CIKM ’24),. ACM; 2024. doi:10.1145/3627673.3679904'
apa: 'Sapkota, R., Köhler, D., & Heindorf, S. (2024). EDGE: Evaluation Framework
for Logical vs. Subgraph Explanations for Node Classifiers on Knowledge Graphs.
Proceedings of the 33rd ACM International Conference on Information and Knowledge
Management (CIKM ’24),. 33rd ACM International Conference on Information and
Knowledge Management, Boise, Idaho, USA. https://doi.org/10.1145/3627673.3679904'
bibtex: '@inproceedings{Sapkota_Köhler_Heindorf_2024, place={Boise, Idaho, USA},
title={EDGE: Evaluation Framework for Logical vs. Subgraph Explanations for Node
Classifiers on Knowledge Graphs}, DOI={10.1145/3627673.3679904},
booktitle={Proceedings of the 33rd ACM International Conference on Information
and Knowledge Management (CIKM ’24),}, publisher={ACM}, author={Sapkota, Rupesh
and Köhler, Dominik and Heindorf, Stefan}, year={2024} }'
chicago: 'Sapkota, Rupesh, Dominik Köhler, and Stefan Heindorf. “EDGE: Evaluation
Framework for Logical vs. Subgraph Explanations for Node Classifiers on Knowledge
Graphs.” In Proceedings of the 33rd ACM International Conference on Information
and Knowledge Management (CIKM ’24),. Boise, Idaho, USA: ACM, 2024. https://doi.org/10.1145/3627673.3679904.'
ieee: 'R. Sapkota, D. Köhler, and S. Heindorf, “EDGE: Evaluation Framework for Logical
vs. Subgraph Explanations for Node Classifiers on Knowledge Graphs,” presented
at the 33rd ACM International Conference on Information and Knowledge Management,
Boise, Idaho, USA, 2024, doi: 10.1145/3627673.3679904.'
mla: 'Sapkota, Rupesh, et al. “EDGE: Evaluation Framework for Logical vs. Subgraph
Explanations for Node Classifiers on Knowledge Graphs.” Proceedings of the
33rd ACM International Conference on Information and Knowledge Management (CIKM
’24), ACM, 2024, doi:10.1145/3627673.3679904.'
short: 'R. Sapkota, D. Köhler, S. Heindorf, in: Proceedings of the 33rd ACM International
Conference on Information and Knowledge Management (CIKM ’24), ACM, Boise, Idaho,
USA, 2024.'
conference:
end_date: 2024-10-25
location: Boise, Idaho, USA
name: 33rd ACM International Conference on Information and Knowledge Management
start_date: 2024-10-21
date_created: 2024-09-23T12:30:10Z
date_updated: 2024-09-23T12:30:25Z
department:
- _id: '760'
- _id: '574'
doi: 10.1145/3627673.3679904
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://papers.dice-research.org/2024/CIKM_EDGE/public.pdf
oa: '1'
place: Boise, Idaho, USA
project:
- _id: '285'
grant_number: NW21-059D
name: 'SAIL: SAIL - Nachhaltiger Lebenszyklus von intelligenten soziotechnischen
Systemen'
publication: Proceedings of the 33rd ACM International Conference on Information and
Knowledge Management (CIKM ’24),
publisher: ACM
status: public
title: 'EDGE: Evaluation Framework for Logical vs. Subgraph Explanations for Node
Classifiers on Knowledge Graphs'
type: conference
user_id: '11871'
year: '2024'
...
---
_id: '56214'
author:
- first_name: Jiayi
full_name: Li, Jiayi
last_name: Li
- first_name: Sheetal
full_name: Satheesh, Sheetal
last_name: Satheesh
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Diego
full_name: Moussallem, Diego
id: '71635'
last_name: Moussallem
- first_name: René
full_name: Speck, René
id: '70843'
last_name: Speck
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Li J, Satheesh S, Heindorf S, Moussallem D, Speck R, Ngonga Ngomo A-C. AutoCL:
AutoML for Concept Learning. In: Communications in Computer and Information
Science. Springer Nature Switzerland; 2024. doi:10.1007/978-3-031-63787-2_7'
apa: 'Li, J., Satheesh, S., Heindorf, S., Moussallem, D., Speck, R., & Ngonga
Ngomo, A.-C. (2024). AutoCL: AutoML for Concept Learning. In Communications
in Computer and Information Science. The 2nd World Conference on eXplainable
Artificial Intelligence, Malta, Valletta. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-63787-2_7'
bibtex: '@inbook{Li_Satheesh_Heindorf_Moussallem_Speck_Ngonga Ngomo_2024, place={Cham},
title={AutoCL: AutoML for Concept Learning}, DOI={10.1007/978-3-031-63787-2_7},
booktitle={Communications in Computer and Information Science}, publisher={Springer
Nature Switzerland}, author={Li, Jiayi and Satheesh, Sheetal and Heindorf, Stefan
and Moussallem, Diego and Speck, René and Ngonga Ngomo, Axel-Cyrille}, year={2024}
}'
chicago: 'Li, Jiayi, Sheetal Satheesh, Stefan Heindorf, Diego Moussallem, René Speck,
and Axel-Cyrille Ngonga Ngomo. “AutoCL: AutoML for Concept Learning.” In Communications
in Computer and Information Science. Cham: Springer Nature Switzerland, 2024.
https://doi.org/10.1007/978-3-031-63787-2_7.'
ieee: 'J. Li, S. Satheesh, S. Heindorf, D. Moussallem, R. Speck, and A.-C. Ngonga
Ngomo, “AutoCL: AutoML for Concept Learning,” in Communications in Computer
and Information Science, Cham: Springer Nature Switzerland, 2024.'
mla: 'Li, Jiayi, et al. “AutoCL: AutoML for Concept Learning.” Communications
in Computer and Information Science, Springer Nature Switzerland, 2024, doi:10.1007/978-3-031-63787-2_7.'
short: 'J. Li, S. Satheesh, S. Heindorf, D. Moussallem, R. Speck, A.-C. Ngonga Ngomo,
in: Communications in Computer and Information Science, Springer Nature Switzerland,
Cham, 2024.'
conference:
end_date: 2024-07-19
location: Malta, Valletta
name: The 2nd World Conference on eXplainable Artificial Intelligence
start_date: 2024-07-17
date_created: 2024-09-23T12:31:23Z
date_updated: 2024-09-23T12:36:17Z
department:
- _id: '760'
- _id: '574'
doi: 10.1007/978-3-031-63787-2_7
language:
- iso: eng
place: Cham
publication: Communications in Computer and Information Science
publication_identifier:
isbn:
- '9783031637865'
- '9783031637872'
issn:
- 1865-0929
- 1865-0937
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: 'AutoCL: AutoML for Concept Learning'
type: book_chapter
user_id: '11871'
year: '2024'
...
---
_id: '55653'
abstract:
- lang: eng
text: We consider the problem of class expression learning using cardinality-minimal
sets of examples. Recent class expression learning approaches employ deep neural
networks and have demonstrated tremendous performance improvements in execution
time and quality of the computed solutions. However, they lack generalization
capabilities when it comes to the number of examples used in a learning problem,
i.e., they often perform poorly on unseen learning problems where only a few examples
are given. In this work, we propose a generalization of the classical class expression
learning problem to address the limitations above. In short, our generalized learning
problem (GLP) forces learning systems to solve the classical class expression
learning problem using the smallest possible subsets of examples, thereby improving
the learning systems' ability to solve unseen learning problems with arbitrary
numbers of examples. Moreover, we develop ROCES, a learning algorithm for synthesis-based
approaches to solve GLP. Experimental results suggest that post training, ROCES
outperforms existing synthesis-based approaches on out-of-distribution learning
problems while remaining highly competitive overall.
author:
- first_name: N'Dah Jean
full_name: KOUAGOU, N'Dah Jean
id: '87189'
last_name: KOUAGOU
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Caglar
full_name: Demir, Caglar
id: '43817'
last_name: Demir
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'KOUAGOU NJ, Heindorf S, Demir C, Ngonga Ngomo A-C. ROCES: Robust Class Expression
Synthesis in Description Logics via Iterative Sampling. In: Proceedings of
the Thirty-ThirdInternational Joint Conference on Artificial Intelligence.
International Joint Conferences on Artificial Intelligence Organization; 2024.
doi:10.24963/ijcai.2024/479'
apa: 'KOUAGOU, N. J., Heindorf, S., Demir, C., & Ngonga Ngomo, A.-C. (2024).
ROCES: Robust Class Expression Synthesis in Description Logics via Iterative Sampling.
Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial
Intelligence. https://doi.org/10.24963/ijcai.2024/479'
bibtex: '@inproceedings{KOUAGOU_Heindorf_Demir_Ngonga Ngomo_2024, title={ROCES:
Robust Class Expression Synthesis in Description Logics via Iterative Sampling},
DOI={10.24963/ijcai.2024/479},
booktitle={Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial
Intelligence}, publisher={International Joint Conferences on Artificial Intelligence
Organization}, author={KOUAGOU, N’Dah Jean and Heindorf, Stefan and Demir, Caglar
and Ngonga Ngomo, Axel-Cyrille}, year={2024} }'
chicago: 'KOUAGOU, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga
Ngomo. “ROCES: Robust Class Expression Synthesis in Description Logics via Iterative
Sampling.” In Proceedings of the Thirty-ThirdInternational Joint Conference
on Artificial Intelligence. International Joint Conferences on Artificial
Intelligence Organization, 2024. https://doi.org/10.24963/ijcai.2024/479.'
ieee: 'N. J. KOUAGOU, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “ROCES: Robust
Class Expression Synthesis in Description Logics via Iterative Sampling,” 2024,
doi: 10.24963/ijcai.2024/479.'
mla: 'KOUAGOU, N’Dah Jean, et al. “ROCES: Robust Class Expression Synthesis in Description
Logics via Iterative Sampling.” Proceedings of the Thirty-ThirdInternational
Joint Conference on Artificial Intelligence, International Joint Conferences
on Artificial Intelligence Organization, 2024, doi:10.24963/ijcai.2024/479.'
short: 'N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: Proceedings
of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence,
International Joint Conferences on Artificial Intelligence Organization, 2024.'
date_created: 2024-08-19T12:43:55Z
date_updated: 2025-07-18T15:52:39Z
ddc:
- '000'
doi: 10.24963/ijcai.2024/479
file:
- access_level: closed
content_type: application/pdf
creator: nkouagou
date_created: 2025-06-26T08:06:07Z
date_updated: 2025-06-26T08:06:07Z
file_id: '60394'
file_name: public.pdf
file_size: 400277
relation: main_file
success: 1
file_date_updated: 2025-06-26T08:06:07Z
has_accepted_license: '1'
language:
- iso: eng
publication: Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial
Intelligence
publication_status: published
publisher: International Joint Conferences on Artificial Intelligence Organization
status: public
title: 'ROCES: Robust Class Expression Synthesis in Description Logics via Iterative
Sampling'
type: conference
user_id: '11871'
year: '2024'
...
---
_id: '46460'
author:
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
- first_name: Caglar
full_name: Demir, Caglar
id: '43817'
last_name: Demir
- first_name: N'Dah Jean
full_name: Kouagou, N'Dah Jean
id: '87189'
last_name: Kouagou
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Nikoloas
full_name: Karalis, Nikoloas
last_name: Karalis
- first_name: Alexander
full_name: Bigerl, Alexander
id: '72857'
last_name: Bigerl
citation:
ama: 'Ngonga Ngomo A-C, Demir C, Kouagou NJ, Heindorf S, Karalis N, Bigerl A. Class
Expression Learning with Multiple Representations. In: Compendium of Neurosymbolic
Artificial Intelligence. IOS Press; 2023:272–286.'
apa: Ngonga Ngomo, A.-C., Demir, C., Kouagou, N. J., Heindorf, S., Karalis, N.,
& Bigerl, A. (2023). Class Expression Learning with Multiple Representations.
In Compendium of Neurosymbolic Artificial Intelligence (pp. 272–286). IOS
Press.
bibtex: '@inbook{Ngonga Ngomo_Demir_Kouagou_Heindorf_Karalis_Bigerl_2023, title={Class
Expression Learning with Multiple Representations}, booktitle={Compendium of Neurosymbolic
Artificial Intelligence}, publisher={IOS Press}, author={Ngonga Ngomo, Axel-Cyrille
and Demir, Caglar and Kouagou, N’Dah Jean and Heindorf, Stefan and Karalis, Nikoloas
and Bigerl, Alexander}, year={2023}, pages={272–286} }'
chicago: Ngonga Ngomo, Axel-Cyrille, Caglar Demir, N’Dah Jean Kouagou, Stefan Heindorf,
Nikoloas Karalis, and Alexander Bigerl. “Class Expression Learning with Multiple
Representations.” In Compendium of Neurosymbolic Artificial Intelligence,
272–286. IOS Press, 2023.
ieee: A.-C. Ngonga Ngomo, C. Demir, N. J. Kouagou, S. Heindorf, N. Karalis, and
A. Bigerl, “Class Expression Learning with Multiple Representations,” in Compendium
of Neurosymbolic Artificial Intelligence, IOS Press, 2023, pp. 272–286.
mla: Ngonga Ngomo, Axel-Cyrille, et al. “Class Expression Learning with Multiple
Representations.” Compendium of Neurosymbolic Artificial Intelligence,
IOS Press, 2023, pp. 272–286.
short: 'A.-C. Ngonga Ngomo, C. Demir, N.J. Kouagou, S. Heindorf, N. Karalis, A.
Bigerl, in: Compendium of Neurosymbolic Artificial Intelligence, IOS Press, 2023,
pp. 272–286.'
date_created: 2023-08-08T11:49:51Z
date_updated: 2023-11-21T08:06:20Z
department:
- _id: '760'
- _id: '574'
language:
- iso: eng
page: 272–286
publication: Compendium of Neurosymbolic Artificial Intelligence
publisher: IOS Press
status: public
title: Class Expression Learning with Multiple Representations
type: book_chapter
user_id: '14931'
year: '2023'
...
---
_id: '46248'
author:
- first_name: Caglar
full_name: Demir, Caglar
id: '43817'
last_name: Demir
- first_name: Michel
full_name: Wiebesiek, Michel
last_name: Wiebesiek
- first_name: Renzhong
full_name: Lu, Renzhong
last_name: Lu
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
citation:
ama: 'Demir C, Wiebesiek M, Lu R, Ngonga Ngomo A-C, Heindorf S. LitCQD: Multi-Hop
Reasoning in Incomplete Knowledge Graphs with Numeric Literals. ECML PKDD.
Published online 2023.'
apa: 'Demir, C., Wiebesiek, M., Lu, R., Ngonga Ngomo, A.-C., & Heindorf, S.
(2023). LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric
Literals. ECML PKDD. European Conference on Machine Learning and Principles
and Practice of Knowledge Discovery in Databases, Torino.'
bibtex: '@article{Demir_Wiebesiek_Lu_Ngonga Ngomo_Heindorf_2023, title={LitCQD:
Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals}, journal={ECML
PKDD}, author={Demir, Caglar and Wiebesiek, Michel and Lu, Renzhong and Ngonga
Ngomo, Axel-Cyrille and Heindorf, Stefan}, year={2023} }'
chicago: 'Demir, Caglar, Michel Wiebesiek, Renzhong Lu, Axel-Cyrille Ngonga Ngomo,
and Stefan Heindorf. “LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs
with Numeric Literals.” ECML PKDD, 2023.'
ieee: 'C. Demir, M. Wiebesiek, R. Lu, A.-C. Ngonga Ngomo, and S. Heindorf, “LitCQD:
Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals,” ECML
PKDD, 2023.'
mla: 'Demir, Caglar, et al. “LitCQD: Multi-Hop Reasoning in Incomplete Knowledge
Graphs with Numeric Literals.” ECML PKDD, 2023.'
short: C. Demir, M. Wiebesiek, R. Lu, A.-C. Ngonga Ngomo, S. Heindorf, ECML PKDD
(2023).
conference:
location: Torino
name: European Conference on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases
date_created: 2023-08-01T09:24:21Z
date_updated: 2024-03-06T16:18:53Z
ddc:
- '000'
department:
- _id: '574'
- _id: '760'
file:
- access_level: open_access
content_type: application/pdf
creator: cdemir
date_created: 2023-08-01T09:24:15Z
date_updated: 2023-08-01T09:24:15Z
file_id: '46249'
file_name: public.pdf
file_size: 562759
relation: main_file
file_date_updated: 2023-08-01T09:24:15Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
project:
- _id: '407'
grant_number: '101070305'
name: 'ENEXA: Efficient Explainable Learning on Knowledge Graphs'
- _id: '410'
grant_number: '860801'
name: 'KnowGraphs: KnowGraphs: Knowledge Graphs at Scale'
- _id: '285'
grant_number: NW21-059D
name: 'SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems'
publication: ECML PKDD
status: public
title: 'LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals'
type: journal_article
user_id: '14931'
year: '2023'
...
---
_id: '47421'
abstract:
- lang: eng
text: Class expression learning in description logics has long been regarded as
an iterative search problem in an infinite conceptual space. Each iteration of
the search process invokes a reasoner and a heuristic function. The reasoner finds
the instances of the current expression, and the heuristic function computes the
information gain and decides on the next step to be taken. As the size of the
background knowledge base grows, search-based approaches for class expression
learning become prohibitively slow. Current neural class expression synthesis
(NCES) approaches investigate the use of neural networks for class expression
learning in the attributive language with complement (ALC). While they show significant
improvements over search-based approaches in runtime and quality of the computed
solutions, they rely on the availability of pretrained embeddings for the input
knowledge base. Moreover, they are not applicable to ontologies in more expressive
description logics. In this paper, we propose a novel NCES approach which extends
the state of the art to the description logic ALCHIQ(D). Our extension, dubbed
NCES2, comes with an improved training data generator and does not require pretrained
embeddings for the input knowledge base as both the embedding model and the class
expression synthesizer are trained jointly. Empirical results on benchmark datasets
suggest that our approach inherits the scalability capability of current NCES
instances with the additional advantage that it supports more complex learning
problems. NCES2 achieves the highest performance overall when compared to search-based
approaches and to its predecessor NCES. We provide our source code, datasets,
and pretrained models at https://github.com/dice-group/NCES2.
author:
- first_name: N'Dah Jean
full_name: Kouagou, N'Dah Jean
id: '87189'
last_name: Kouagou
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Caglar
full_name: Demir, Caglar
id: '43817'
last_name: Demir
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Kouagou NJ, Heindorf S, Demir C, Ngonga Ngomo A-C. Neural Class Expression
Synthesis in ALCHIQ(D). In: Machine Learning and Knowledge Discovery in Databases:
Research Track. Springer Nature Switzerland; 2023. doi:10.1007/978-3-031-43421-1_12'
apa: 'Kouagou, N. J., Heindorf, S., Demir, C., & Ngonga Ngomo, A.-C. (2023).
Neural Class Expression Synthesis in ALCHIQ(D). In Machine Learning and Knowledge
Discovery in Databases: Research Track. European Conference on Machine Learning
and Principles and Practice of Knowledge Discovery in Databases, Turin. Springer
Nature Switzerland. https://doi.org/10.1007/978-3-031-43421-1_12'
bibtex: '@inbook{Kouagou_Heindorf_Demir_Ngonga Ngomo_2023, place={Cham}, title={Neural
Class Expression Synthesis in ALCHIQ(D)}, DOI={10.1007/978-3-031-43421-1_12},
booktitle={Machine Learning and Knowledge Discovery in Databases: Research Track},
publisher={Springer Nature Switzerland}, author={Kouagou, N’Dah Jean and Heindorf,
Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2023} }'
chicago: 'Kouagou, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga
Ngomo. “Neural Class Expression Synthesis in ALCHIQ(D).” In Machine Learning
and Knowledge Discovery in Databases: Research Track. Cham: Springer Nature
Switzerland, 2023. https://doi.org/10.1007/978-3-031-43421-1_12.'
ieee: 'N. J. Kouagou, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Neural Class
Expression Synthesis in ALCHIQ(D),” in Machine Learning and Knowledge Discovery
in Databases: Research Track, Cham: Springer Nature Switzerland, 2023.'
mla: 'Kouagou, N’Dah Jean, et al. “Neural Class Expression Synthesis in ALCHIQ(D).”
Machine Learning and Knowledge Discovery in Databases: Research Track,
Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-43421-1_12.'
short: 'N.J. Kouagou, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: Machine Learning
and Knowledge Discovery in Databases: Research Track, Springer Nature Switzerland,
Cham, 2023.'
conference:
end_date: 2023-09-22
location: Turin
name: European Conference on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases
start_date: 2023-09-18
date_created: 2023-09-25T13:42:01Z
date_updated: 2024-05-22T10:48:24Z
ddc:
- '000'
department:
- _id: '760'
- _id: '574'
doi: 10.1007/978-3-031-43421-1_12
file:
- access_level: open_access
content_type: application/pdf
creator: heindorf
date_created: 2024-05-22T10:45:08Z
date_updated: 2024-05-22T10:46:58Z
file_id: '54417'
file_name: NCES2_public.pdf
file_size: 432708
relation: main_file
file_date_updated: 2024-05-22T10:46:58Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://papers.dice-research.org/2023/ECML_NCES2/NCES2_public.pdf
oa: '1'
place: Cham
publication: 'Machine Learning and Knowledge Discovery in Databases: Research Track'
publication_identifier:
isbn:
- '9783031434204'
- '9783031434211'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: Neural Class Expression Synthesis in ALCHIQ(D)
type: book_chapter
user_id: '11871'
year: '2023'
...
---
_id: '37937'
abstract:
- lang: eng
text: "Knowledge bases are widely used for information management on the web,\r\nenabling
high-impact applications such as web search, question answering, and\r\nnatural
language processing. They also serve as the backbone for automatic\r\ndecision
systems, e.g. for medical diagnostics and credit scoring. As\r\nstakeholders affected
by these decisions would like to understand their\r\nsituation and verify fair
decisions, a number of explanation approaches have\r\nbeen proposed using concepts
in description logics. However, the learned\r\nconcepts can become long and difficult
to fathom for non-experts, even when\r\nverbalized. Moreover, long concepts do
not immediately provide a clear path of\r\naction to change one's situation. Counterfactuals
answering the question \"How\r\nmust feature values be changed to obtain a different
classification?\" have been\r\nproposed as short, human-friendly explanations
for tabular data. In this paper,\r\nwe transfer the notion of counterfactuals
to description logics and propose the\r\nfirst algorithm for generating counterfactual
explanations in the description\r\nlogic $\\mathcal{ELH}$. Counterfactual candidates
are generated from concepts\r\nand the candidates with fewest feature changes
are selected as counterfactuals.\r\nIn case of multiple counterfactuals, we rank
them according to the likeliness\r\nof their feature combinations. For evaluation,
we conduct a user survey to\r\ninvestigate which of the generated counterfactual
candidates are preferred for\r\nexplanation by participants. In a second study,
we explore possible use cases\r\nfor counterfactual explanations."
author:
- first_name: Leonie Nora
full_name: Sieger, Leonie Nora
id: '93402'
last_name: Sieger
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Lukas
full_name: Blübaum, Lukas
last_name: Blübaum
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: Sieger LN, Heindorf S, Blübaum L, Ngonga Ngomo A-C. Explaining ELH Concept
Descriptions through Counterfactual Reasoning. arXiv:230105109. Published
online 2023.
apa: Sieger, L. N., Heindorf, S., Blübaum, L., & Ngonga Ngomo, A.-C. (2023).
Explaining ELH Concept Descriptions through Counterfactual Reasoning. In arXiv:2301.05109.
bibtex: '@article{Sieger_Heindorf_Blübaum_Ngonga Ngomo_2023, title={Explaining ELH
Concept Descriptions through Counterfactual Reasoning}, journal={arXiv:2301.05109},
author={Sieger, Leonie Nora and Heindorf, Stefan and Blübaum, Lukas and Ngonga
Ngomo, Axel-Cyrille}, year={2023} }'
chicago: Sieger, Leonie Nora, Stefan Heindorf, Lukas Blübaum, and Axel-Cyrille Ngonga
Ngomo. “Explaining ELH Concept Descriptions through Counterfactual Reasoning.”
ArXiv:2301.05109, 2023.
ieee: L. N. Sieger, S. Heindorf, L. Blübaum, and A.-C. Ngonga Ngomo, “Explaining
ELH Concept Descriptions through Counterfactual Reasoning,” arXiv:2301.05109.
2023.
mla: Sieger, Leonie Nora, et al. “Explaining ELH Concept Descriptions through Counterfactual
Reasoning.” ArXiv:2301.05109, 2023.
short: L.N. Sieger, S. Heindorf, L. Blübaum, A.-C. Ngonga Ngomo, ArXiv:2301.05109
(2023).
date_created: 2023-01-22T19:36:01Z
date_updated: 2024-05-26T19:03:44Z
department:
- _id: '574'
- _id: '760'
external_id:
arxiv:
- '2301.05109'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/pdf/2301.05109.pdf
oa: '1'
publication: arXiv:2301.05109
status: public
title: Explaining ELH Concept Descriptions through Counterfactual Reasoning
type: preprint
user_id: '11871'
year: '2023'
...
---
_id: '54612'
author:
- first_name: N'Dah Jean
full_name: KOUAGOU, N'Dah Jean
id: '87189'
last_name: KOUAGOU
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Caglar
full_name: Demir, Caglar
id: '43817'
last_name: Demir
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'KOUAGOU NJ, Heindorf S, Demir C, Ngonga Ngomo A-C. Neural Class Expression
Synthesis (Extended Abstract). In: NeSy 2023, 17th International Workshop on
Neural-Symbolic Learning and Reasoning, Certosa Di Pontignano, Siena, Italy.
CEUR-WS; 2023.'
apa: KOUAGOU, N. J., Heindorf, S., Demir, C., & Ngonga Ngomo, A.-C. (2023).
Neural Class Expression Synthesis (Extended Abstract). NeSy 2023, 17th International
Workshop on Neural-Symbolic Learning and Reasoning, Certosa Di Pontignano, Siena,
Italy.
bibtex: '@inproceedings{KOUAGOU_Heindorf_Demir_Ngonga Ngomo_2023, title={Neural
Class Expression Synthesis (Extended Abstract)}, booktitle={NeSy 2023, 17th International
Workshop on Neural-Symbolic Learning and Reasoning, Certosa di Pontignano, Siena,
Italy}, publisher={CEUR-WS}, author={KOUAGOU, N’Dah Jean and Heindorf, Stefan
and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2023} }'
chicago: KOUAGOU, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga
Ngomo. “Neural Class Expression Synthesis (Extended Abstract).” In NeSy 2023,
17th International Workshop on Neural-Symbolic Learning and Reasoning, Certosa
Di Pontignano, Siena, Italy. CEUR-WS, 2023.
ieee: N. J. KOUAGOU, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Neural Class
Expression Synthesis (Extended Abstract),” 2023.
mla: KOUAGOU, N’Dah Jean, et al. “Neural Class Expression Synthesis (Extended Abstract).”
NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning,
Certosa Di Pontignano, Siena, Italy, CEUR-WS, 2023.
short: 'N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: NeSy 2023,
17th International Workshop on Neural-Symbolic Learning and Reasoning, Certosa
Di Pontignano, Siena, Italy, CEUR-WS, 2023.'
date_created: 2024-06-04T15:36:52Z
date_updated: 2024-06-04T15:40:30Z
department:
- _id: '574'
- _id: '760'
keyword:
- 318 SFB-TRR demir dice enexa heindorf knowgraphs kouagou ngonga sail
language:
- iso: eng
publication: NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and
Reasoning, Certosa di Pontignano, Siena, Italy
publisher: CEUR-WS
status: public
title: Neural Class Expression Synthesis (Extended Abstract)
type: conference
user_id: '67199'
year: '2023'
...
---
_id: '33734'
abstract:
- lang: eng
text: 'Many applications require explainable node classification in knowledge graphs.
Towards this end, a popular ``white-box'''' approach is class expression learning:
Given sets of positive and negative nodes, class expressions in description logics
are learned that separate positive from negative nodes. Most existing approaches
are search-based approaches generating many candidate class expressions and selecting
the best one. However, they often take a long time to find suitable class expressions.
In this paper, we cast class expression learning as a translation problem and
propose a new family of class expression learning approaches which we dub neural
class expression synthesizers. Training examples are ``translated'''' into class
expressions in a fashion akin to machine translation. Consequently, our synthesizers
are not subject to the runtime limitations of search-based approaches. We study
three instances of this novel family of approaches based on LSTMs, GRUs, and set
transformers, respectively. An evaluation of our approach on four benchmark datasets
suggests that it can effectively synthesize high-quality class expressions with
respect to the input examples in approximately one second on average. Moreover,
a comparison to state-of-the-art approaches suggests that we achieve better F-measures
on large datasets. For reproducibility purposes, we provide our implementation
as well as pretrained models in our public GitHub repository at https://github.com/dice-group/NeuralClassExpressionSynthesis'
author:
- first_name: N'Dah Jean
full_name: KOUAGOU, N'Dah Jean
id: '87189'
last_name: KOUAGOU
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Caglar
full_name: Demir, Caglar
id: '43817'
last_name: Demir
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'KOUAGOU NJ, Heindorf S, Demir C, Ngonga Ngomo A-C. Neural Class Expression
Synthesis. In: Pesquita C, Jimenez-Ruiz E, McCusker J, et al., eds. The Semantic
Web - 20th Extended Semantic Web Conference (ESWC 2023). Vol 13870. Springer
International Publishing; 2023:209-226. doi:https://doi.org/10.1007/978-3-031-33455-9_13'
apa: KOUAGOU, N. J., Heindorf, S., Demir, C., & Ngonga Ngomo, A.-C. (2023).
Neural Class Expression Synthesis. In C. Pesquita, E. Jimenez-Ruiz, J. McCusker,
D. Faria, M. Dragoni, A. Dimou, R. Troncy, & S. Hertling (Eds.), The Semantic
Web - 20th Extended Semantic Web Conference (ESWC 2023) (Vol. 13870, pp. 209–226).
Springer International Publishing. https://doi.org/10.1007/978-3-031-33455-9_13
bibtex: '@inproceedings{KOUAGOU_Heindorf_Demir_Ngonga Ngomo_2023, title={Neural
Class Expression Synthesis}, volume={13870}, DOI={https://doi.org/10.1007/978-3-031-33455-9_13},
booktitle={The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)},
publisher={Springer International Publishing}, author={KOUAGOU, N’Dah Jean and
Heindorf, Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, editor={Pesquita,
Catia and Jimenez-Ruiz, Ernesto and McCusker, Jamie and Faria, Daniel and Dragoni,
Mauro and Dimou, Anastasia and Troncy, Raphael and Hertling, Sven}, year={2023},
pages={209–226} }'
chicago: KOUAGOU, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga
Ngomo. “Neural Class Expression Synthesis.” In The Semantic Web - 20th Extended
Semantic Web Conference (ESWC 2023), edited by Catia Pesquita, Ernesto Jimenez-Ruiz,
Jamie McCusker, Daniel Faria, Mauro Dragoni, Anastasia Dimou, Raphael Troncy,
and Sven Hertling, 13870:209–26. Springer International Publishing, 2023. https://doi.org/10.1007/978-3-031-33455-9_13.
ieee: 'N. J. KOUAGOU, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Neural Class
Expression Synthesis,” in The Semantic Web - 20th Extended Semantic Web Conference
(ESWC 2023), Hersonissos, Crete, Greece, 2023, vol. 13870, pp. 209–226, doi:
https://doi.org/10.1007/978-3-031-33455-9_13.'
mla: KOUAGOU, N’Dah Jean, et al. “Neural Class Expression Synthesis.” The Semantic
Web - 20th Extended Semantic Web Conference (ESWC 2023), edited by Catia Pesquita
et al., vol. 13870, Springer International Publishing, 2023, pp. 209–26, doi:https://doi.org/10.1007/978-3-031-33455-9_13.
short: 'N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: C. Pesquita,
E. Jimenez-Ruiz, J. McCusker, D. Faria, M. Dragoni, A. Dimou, R. Troncy, S. Hertling
(Eds.), The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023),
Springer International Publishing, 2023, pp. 209–226.'
conference:
end_date: 2023-06-01
location: Hersonissos, Crete, Greece
name: 20th Extended Semantic Web Conference
start_date: 2023-05-28
date_created: 2022-10-15T19:20:11Z
date_updated: 2023-07-02T18:10:02Z
department:
- _id: '574'
- _id: '760'
doi: https://doi.org/10.1007/978-3-031-33455-9_13
editor:
- first_name: Catia
full_name: Pesquita, Catia
last_name: Pesquita
- first_name: Ernesto
full_name: Jimenez-Ruiz, Ernesto
last_name: Jimenez-Ruiz
- first_name: Jamie
full_name: McCusker, Jamie
last_name: McCusker
- first_name: Daniel
full_name: Faria, Daniel
last_name: Faria
- first_name: Mauro
full_name: Dragoni, Mauro
last_name: Dragoni
- first_name: Anastasia
full_name: Dimou, Anastasia
last_name: Dimou
- first_name: Raphael
full_name: Troncy, Raphael
last_name: Troncy
- first_name: Sven
full_name: Hertling, Sven
last_name: Hertling
external_id:
unknown:
- https://link.springer.com/chapter/10.1007/978-3-031-33455-9_13
intvolume: ' 13870'
keyword:
- Neural network
- Concept learning
- Description logics
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://2023.eswc-conferences.org/wp-content/uploads/2023/05/paper_Kouagou_2023_Neural.pdf
oa: '1'
page: 209 - 226
project:
- _id: '410'
name: 'KnowGraphs: KnowGraphs: Knowledge Graphs at Scale'
- _id: '407'
grant_number: '101070305'
name: 'ENEXA: Efficient Explainable Learning on Knowledge Graphs'
- _id: '285'
grant_number: NW21-059D
name: 'SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems'
publication: The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)
publication_identifier:
unknown:
- 978-3-031-33455-9
publication_status: published
publisher: Springer International Publishing
status: public
title: Neural Class Expression Synthesis
type: conference
user_id: '11871'
volume: 13870
year: '2023'
...
---
_id: '46575'
author:
- first_name: Alkid
full_name: Baci, Alkid
id: '92869'
last_name: Baci
orcid: 0009-0001-3279-0161
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
citation:
ama: 'Baci A, Heindorf S. Accelerating Concept Learning via Sampling. In: CIKM.
; 2023:3733–3737. doi:10.1145/3583780.3615158'
apa: Baci, A., & Heindorf, S. (2023). Accelerating Concept Learning via Sampling.
CIKM, 3733–3737. https://doi.org/10.1145/3583780.3615158
bibtex: '@inproceedings{Baci_Heindorf_2023, title={Accelerating Concept Learning
via Sampling}, DOI={10.1145/3583780.3615158},
booktitle={CIKM}, author={Baci, Alkid and Heindorf, Stefan}, year={2023}, pages={3733–3737}
}'
chicago: Baci, Alkid, and Stefan Heindorf. “Accelerating Concept Learning via Sampling.”
In CIKM, 3733–3737, 2023. https://doi.org/10.1145/3583780.3615158.
ieee: 'A. Baci and S. Heindorf, “Accelerating Concept Learning via Sampling,” in
CIKM, Birmingham, UK, 2023, pp. 3733–3737, doi: 10.1145/3583780.3615158.'
mla: Baci, Alkid, and Stefan Heindorf. “Accelerating Concept Learning via Sampling.”
CIKM, 2023, pp. 3733–3737, doi:10.1145/3583780.3615158.
short: 'A. Baci, S. Heindorf, in: CIKM, 2023, pp. 3733–3737.'
conference:
end_date: 2023-10-25
location: Birmingham, UK
start_date: 2023-10-21
date_created: 2023-08-19T08:02:54Z
date_updated: 2024-11-29T12:33:19Z
ddc:
- '000'
department:
- _id: '760'
doi: 10.1145/3583780.3615158
file:
- access_level: open_access
content_type: application/pdf
creator: heindorf
date_created: 2023-08-19T08:08:39Z
date_updated: 2023-08-19T08:08:39Z
file_id: '46577'
file_name: baci2023_CIKM.pdf
file_size: 523067
relation: main_file
file_date_updated: 2023-08-19T08:08:39Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
page: 3733–3737
publication: CIKM
status: public
title: Accelerating Concept Learning via Sampling
type: conference
user_id: '11871'
year: '2023'
...
---
_id: '33957'
abstract:
- lang: eng
text: Manufacturing companies are challenged to make the increasingly complex work
processes equally manageable for all employees to prevent an impending loss of
competence. In this contribution, an intelligent assistance system is proposed
enabling employees to help themselves in the workplace and provide them with competence-related
support. This results in increasing the short- and long-term efficiency of problem
solving in companies.
author:
- first_name: Sahar
full_name: Deppe, Sahar
last_name: Deppe
- first_name: Lukas
full_name: Brandt, Lukas
last_name: Brandt
- first_name: Marc
full_name: Brünninghaus, Marc
last_name: Brünninghaus
- first_name: Jörg
full_name: Papenkordt, Jörg
id: '44648'
last_name: Papenkordt
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Gudrun
full_name: Tschirner-Vinke, Gudrun
last_name: Tschirner-Vinke
citation:
ama: Deppe S, Brandt L, Brünninghaus M, Papenkordt J, Heindorf S, Tschirner-Vinke
G. AI-Based Assistance System for Manufacturing. Published online 2022. doi:10.1109/ETFA52439.2022.9921520
apa: Deppe, S., Brandt, L., Brünninghaus, M., Papenkordt, J., Heindorf, S., &
Tschirner-Vinke, G. (2022). AI-Based Assistance System for Manufacturing.
ETFA, Stuttgart. https://doi.org/10.1109/ETFA52439.2022.9921520
bibtex: '@article{Deppe_Brandt_Brünninghaus_Papenkordt_Heindorf_Tschirner-Vinke_2022,
series={2022 IEEE 27th International Conference on Emerging Technologies and Factory
Automation (ETFA)}, title={AI-Based Assistance System for Manufacturing}, DOI={10.1109/ETFA52439.2022.9921520},
author={Deppe, Sahar and Brandt, Lukas and Brünninghaus, Marc and Papenkordt,
Jörg and Heindorf, Stefan and Tschirner-Vinke, Gudrun}, year={2022}, collection={2022
IEEE 27th International Conference on Emerging Technologies and Factory Automation
(ETFA)} }'
chicago: Deppe, Sahar, Lukas Brandt, Marc Brünninghaus, Jörg Papenkordt, Stefan
Heindorf, and Gudrun Tschirner-Vinke. “AI-Based Assistance System for Manufacturing.”
2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation
(ETFA), 2022. https://doi.org/10.1109/ETFA52439.2022.9921520.
ieee: 'S. Deppe, L. Brandt, M. Brünninghaus, J. Papenkordt, S. Heindorf, and G.
Tschirner-Vinke, “AI-Based Assistance System for Manufacturing.” 2022, doi: 10.1109/ETFA52439.2022.9921520.'
mla: Deppe, Sahar, et al. AI-Based Assistance System for Manufacturing. 2022,
doi:10.1109/ETFA52439.2022.9921520.
short: S. Deppe, L. Brandt, M. Brünninghaus, J. Papenkordt, S. Heindorf, G. Tschirner-Vinke,
(2022).
conference:
end_date: 2022-09-09
location: Stuttgart
name: ETFA
start_date: 2022-09-06
date_created: 2022-10-28T11:43:49Z
date_updated: 2023-11-23T08:07:51Z
department:
- _id: '178'
- _id: '574'
- _id: '184'
doi: 10.1109/ETFA52439.2022.9921520
keyword:
- Assistance system
- Knowledge graph
- Information retrieval
- Neural networks
- AR
language:
- iso: eng
project:
- _id: '409'
grant_number: 02L19C115
name: 'KIAM: KIAM: Kompetenzzentrum KI in der Arbeitswelt des industriellen Mittelstands
in OstWestfalenLippe'
related_material:
link:
- relation: confirmation
url: https://ieeexplore.ieee.org/document/9921520
series_title: 2022 IEEE 27th International Conference on Emerging Technologies and
Factory Automation (ETFA)
status: public
title: AI-Based Assistance System for Manufacturing
type: conference
user_id: '44648'
year: '2022'
...
---
_id: '33740'
author:
- first_name: N'Dah Jean
full_name: KOUAGOU, N'Dah Jean
id: '87189'
last_name: KOUAGOU
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Caglar
full_name: Demir, Caglar
id: '43817'
last_name: Demir
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'KOUAGOU NJ, Heindorf S, Demir C, Ngonga Ngomo A-C. Learning Concept Lengths
Accelerates Concept Learning in ALC. In: The Semantic Web. Springer International
Publishing; 2022. doi:10.1007/978-3-031-06981-9_14'
apa: KOUAGOU, N. J., Heindorf, S., Demir, C., & Ngonga Ngomo, A.-C. (2022).
Learning Concept Lengths Accelerates Concept Learning in ALC. In The Semantic
Web. Springer International Publishing. https://doi.org/10.1007/978-3-031-06981-9_14
bibtex: '@inbook{KOUAGOU_Heindorf_Demir_Ngonga Ngomo_2022, place={Cham}, title={Learning
Concept Lengths Accelerates Concept Learning in ALC}, DOI={10.1007/978-3-031-06981-9_14},
booktitle={The Semantic Web}, publisher={Springer International Publishing}, author={KOUAGOU,
N’Dah Jean and Heindorf, Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille},
year={2022} }'
chicago: 'KOUAGOU, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga
Ngomo. “Learning Concept Lengths Accelerates Concept Learning in ALC.” In The
Semantic Web. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-06981-9_14.'
ieee: 'N. J. KOUAGOU, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Learning Concept
Lengths Accelerates Concept Learning in ALC,” in The Semantic Web, Cham:
Springer International Publishing, 2022.'
mla: KOUAGOU, N’Dah Jean, et al. “Learning Concept Lengths Accelerates Concept Learning
in ALC.” The Semantic Web, Springer International Publishing, 2022, doi:10.1007/978-3-031-06981-9_14.
short: 'N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: The Semantic
Web, Springer International Publishing, Cham, 2022.'
date_created: 2022-10-15T19:34:41Z
date_updated: 2024-04-03T13:26:10Z
department:
- _id: '574'
- _id: '760'
doi: 10.1007/978-3-031-06981-9_14
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2107.04911
oa: '1'
place: Cham
publication: The Semantic Web
publication_identifier:
isbn:
- '9783031069802'
- '9783031069819'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer International Publishing
related_material:
link:
- relation: confirmation
url: https://link.springer.com/chapter/10.1007/978-3-031-06981-9_14
status: public
title: Learning Concept Lengths Accelerates Concept Learning in ALC
type: book_chapter
user_id: '11871'
year: '2022'
...
---
_id: '29290'
abstract:
- lang: eng
text: "Classifying nodes in knowledge graphs is an important task, e.g., predicting\r\nmissing
types of entities, predicting which molecules cause cancer, or\r\npredicting which
drugs are promising treatment candidates. While black-box\r\nmodels often achieve
high predictive performance, they are only post-hoc and\r\nlocally explainable
and do not allow the learned model to be easily enriched\r\nwith domain knowledge.
Towards this end, learning description logic concepts\r\nfrom positive and negative
examples has been proposed. However, learning such\r\nconcepts often takes a long
time and state-of-the-art approaches provide\r\nlimited support for literal data
values, although they are crucial for many\r\napplications. In this paper, we
propose EvoLearner - an evolutionary approach\r\nto learn ALCQ(D), which is the
attributive language with complement (ALC)\r\npaired with qualified cardinality
restrictions (Q) and data properties (D). We\r\ncontribute a novel initialization
method for the initial population: starting\r\nfrom positive examples (nodes in
the knowledge graph), we perform biased random\r\nwalks and translate them to
description logic concepts. Moreover, we improve\r\nsupport for data properties
by maximizing information gain when deciding where\r\nto split the data. We show
that our approach significantly outperforms the\r\nstate of the art on the benchmarking
framework SML-Bench for structured machine\r\nlearning. Our ablation study confirms
that this is due to our novel\r\ninitialization method and support for data properties."
author:
- first_name: Stefan
full_name: Heindorf, Stefan
id: '11871'
last_name: Heindorf
orcid: 0000-0002-4525-6865
- first_name: Lukas
full_name: Blübaum, Lukas
last_name: Blübaum
- first_name: Nick
full_name: Düsterhus, Nick
last_name: Düsterhus
- first_name: Till
full_name: Werner, Till
last_name: Werner
- first_name: Varun Nandkumar
full_name: Golani, Varun Nandkumar
last_name: Golani
- first_name: Caglar
full_name: Demir, Caglar
id: '43817'
last_name: Demir
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: 'Heindorf S, Blübaum L, Düsterhus N, et al. EvoLearner: Learning Description
Logics with Evolutionary Algorithms. In: WWW. ACM; 2022:818-828. doi:10.1145/3485447.3511925'
apa: 'Heindorf, S., Blübaum, L., Düsterhus, N., Werner, T., Golani, V. N., Demir,
C., & Ngonga Ngomo, A.-C. (2022). EvoLearner: Learning Description Logics
with Evolutionary Algorithms. WWW, 818–828. https://doi.org/10.1145/3485447.3511925'
bibtex: '@inproceedings{Heindorf_Blübaum_Düsterhus_Werner_Golani_Demir_Ngonga Ngomo_2022,
title={EvoLearner: Learning Description Logics with Evolutionary Algorithms},
DOI={10.1145/3485447.3511925},
booktitle={WWW}, publisher={ACM}, author={Heindorf, Stefan and Blübaum, Lukas
and Düsterhus, Nick and Werner, Till and Golani, Varun Nandkumar and Demir, Caglar
and Ngonga Ngomo, Axel-Cyrille}, year={2022}, pages={818–828} }'
chicago: 'Heindorf, Stefan, Lukas Blübaum, Nick Düsterhus, Till Werner, Varun Nandkumar
Golani, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “EvoLearner: Learning Description
Logics with Evolutionary Algorithms.” In WWW, 818–28. ACM, 2022. https://doi.org/10.1145/3485447.3511925.'
ieee: 'S. Heindorf et al., “EvoLearner: Learning Description Logics with
Evolutionary Algorithms,” in WWW, 2022, pp. 818–828, doi: 10.1145/3485447.3511925.'
mla: 'Heindorf, Stefan, et al. “EvoLearner: Learning Description Logics with Evolutionary
Algorithms.” WWW, ACM, 2022, pp. 818–28, doi:10.1145/3485447.3511925.'
short: 'S. Heindorf, L. Blübaum, N. Düsterhus, T. Werner, V.N. Golani, C. Demir,
A.-C. Ngonga Ngomo, in: WWW, ACM, 2022, pp. 818–828.'
date_created: 2022-01-12T10:22:53Z
date_updated: 2024-05-26T19:13:09Z
department:
- _id: '574'
doi: 10.1145/3485447.3511925
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2111.04879
oa: '1'
page: 818-828
publication: WWW
publisher: ACM
status: public
title: 'EvoLearner: Learning Description Logics with Evolutionary Algorithms'
type: conference
user_id: '11871'
year: '2022'
...