---
_id: '63572'
author:
- first_name: Caglar
  full_name: Demir, Caglar
  id: '43817'
  last_name: Demir
- first_name: Moshood Olawale
  full_name: Yekini, Moshood Olawale
  id: '114533'
  last_name: Yekini
- first_name: Michael
  full_name: Röder, Michael
  id: '67199'
  last_name: Röder
  orcid: https://orcid.org/0000-0002-8609-8277
- first_name: Yasir
  full_name: Mahmood, Yasir
  id: '99353'
  last_name: Mahmood
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  id: '65716'
  last_name: Ngonga Ngomo
citation:
  ama: 'Demir C, Yekini MO, Röder M, Mahmood Y, Ngonga Ngomo A-C. Tree-Based OWL Class
    Expression Learner over Large Graphs. In: <i>Lecture Notes in Computer Science</i>.
    Springer Nature Switzerland; 2025. doi:<a href="https://doi.org/10.1007/978-3-032-06066-2_29">10.1007/978-3-032-06066-2_29</a>'
  apa: Demir, C., Yekini, M. O., Röder, M., Mahmood, Y., &#38; Ngonga Ngomo, A.-C.
    (2025). Tree-Based OWL Class Expression Learner over Large Graphs. <i>Lecture
    Notes in Computer Science</i>. European Conference on Machine Learning and Principles
    and Practice of Knowledge Discovery in Databases, Porto. <a href="https://doi.org/10.1007/978-3-032-06066-2_29">https://doi.org/10.1007/978-3-032-06066-2_29</a>
  bibtex: '@inproceedings{Demir_Yekini_Röder_Mahmood_Ngonga Ngomo_2025, place={Cham},
    title={Tree-Based OWL Class Expression Learner over Large Graphs}, DOI={<a href="https://doi.org/10.1007/978-3-032-06066-2_29">10.1007/978-3-032-06066-2_29</a>},
    booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland},
    author={Demir, Caglar and Yekini, Moshood Olawale and Röder, Michael and Mahmood,
    Yasir and Ngonga Ngomo, Axel-Cyrille}, year={2025} }'
  chicago: 'Demir, Caglar, Moshood Olawale Yekini, Michael Röder, Yasir Mahmood, and
    Axel-Cyrille Ngonga Ngomo. “Tree-Based OWL Class Expression Learner over Large
    Graphs.” In <i>Lecture Notes in Computer Science</i>. Cham: Springer Nature Switzerland,
    2025. <a href="https://doi.org/10.1007/978-3-032-06066-2_29">https://doi.org/10.1007/978-3-032-06066-2_29</a>.'
  ieee: 'C. Demir, M. O. Yekini, M. Röder, Y. Mahmood, and A.-C. Ngonga Ngomo, “Tree-Based
    OWL Class Expression Learner over Large Graphs,” presented at the European Conference
    on Machine Learning and Principles and Practice of Knowledge Discovery in Databases,
    Porto, 2025, doi: <a href="https://doi.org/10.1007/978-3-032-06066-2_29">10.1007/978-3-032-06066-2_29</a>.'
  mla: Demir, Caglar, et al. “Tree-Based OWL Class Expression Learner over Large Graphs.”
    <i>Lecture Notes in Computer Science</i>, Springer Nature Switzerland, 2025, doi:<a
    href="https://doi.org/10.1007/978-3-032-06066-2_29">10.1007/978-3-032-06066-2_29</a>.
  short: 'C. Demir, M.O. Yekini, M. Röder, Y. Mahmood, A.-C. Ngonga Ngomo, in: Lecture
    Notes in Computer Science, Springer Nature Switzerland, Cham, 2025.'
conference:
  end_date: 2025-09-19
  location: Porto
  name: European Conference on Machine Learning and Principles and Practice of Knowledge
    Discovery in Databases
  start_date: 2025-09-15
date_created: 2026-01-12T17:13:22Z
date_updated: 2026-01-12T17:17:07Z
department:
- _id: '574'
- _id: '923'
doi: 10.1007/978-3-032-06066-2_29
language:
- iso: eng
place: Cham
publication: Lecture Notes in Computer Science
publication_identifier:
  isbn:
  - '9783032060655'
  - '9783032060662'
  issn:
  - 0302-9743
  - 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: Tree-Based OWL Class Expression Learner over Large Graphs
type: conference
user_id: '67199'
year: '2025'
...
---
_id: '63575'
author:
- first_name: Sourabh
  full_name: Kapoor, Sourabh
  last_name: Kapoor
- first_name: Arnab
  full_name: Sharma, Arnab
  id: '67200'
  last_name: Sharma
- first_name: Michael
  full_name: Röder, Michael
  id: '67199'
  last_name: Röder
  orcid: https://orcid.org/0000-0002-8609-8277
- 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: 'Kapoor S, Sharma A, Röder M, Demir C, Ngonga Ngomo A-C. Robustness Evaluation
    of Knowledge Graph Embedding Models Under Non-targeted Attacks. In: <i>Lecture
    Notes in Computer Science</i>. Springer Nature Switzerland; 2025. doi:<a href="https://doi.org/10.1007/978-3-031-94575-5_15">10.1007/978-3-031-94575-5_15</a>'
  apa: Kapoor, S., Sharma, A., Röder, M., Demir, C., &#38; Ngonga Ngomo, A.-C. (2025).
    Robustness Evaluation of Knowledge Graph Embedding Models Under Non-targeted Attacks.
    <i>Lecture Notes in Computer Science</i>. <a href="https://doi.org/10.1007/978-3-031-94575-5_15">https://doi.org/10.1007/978-3-031-94575-5_15</a>
  bibtex: '@inproceedings{Kapoor_Sharma_Röder_Demir_Ngonga Ngomo_2025, place={Cham},
    title={Robustness Evaluation of Knowledge Graph Embedding Models Under Non-targeted
    Attacks}, DOI={<a href="https://doi.org/10.1007/978-3-031-94575-5_15">10.1007/978-3-031-94575-5_15</a>},
    booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland},
    author={Kapoor, Sourabh and Sharma, Arnab and Röder, Michael and Demir, Caglar
    and Ngonga Ngomo, Axel-Cyrille}, year={2025} }'
  chicago: 'Kapoor, Sourabh, Arnab Sharma, Michael Röder, Caglar Demir, and Axel-Cyrille
    Ngonga Ngomo. “Robustness Evaluation of Knowledge Graph Embedding Models Under
    Non-Targeted Attacks.” In <i>Lecture Notes in Computer Science</i>. Cham: Springer
    Nature Switzerland, 2025. <a href="https://doi.org/10.1007/978-3-031-94575-5_15">https://doi.org/10.1007/978-3-031-94575-5_15</a>.'
  ieee: 'S. Kapoor, A. Sharma, M. Röder, C. Demir, and A.-C. Ngonga Ngomo, “Robustness
    Evaluation of Knowledge Graph Embedding Models Under Non-targeted Attacks,” 2025,
    doi: <a href="https://doi.org/10.1007/978-3-031-94575-5_15">10.1007/978-3-031-94575-5_15</a>.'
  mla: Kapoor, Sourabh, et al. “Robustness Evaluation of Knowledge Graph Embedding
    Models Under Non-Targeted Attacks.” <i>Lecture Notes in Computer Science</i>,
    Springer Nature Switzerland, 2025, doi:<a href="https://doi.org/10.1007/978-3-031-94575-5_15">10.1007/978-3-031-94575-5_15</a>.
  short: 'S. Kapoor, A. Sharma, M. Röder, C. Demir, A.-C. Ngonga Ngomo, in: Lecture
    Notes in Computer Science, Springer Nature Switzerland, Cham, 2025.'
date_created: 2026-01-12T17:24:11Z
date_updated: 2026-01-12T17:24:49Z
department:
- _id: '574'
- _id: '923'
doi: 10.1007/978-3-031-94575-5_15
language:
- iso: eng
place: Cham
publication: Lecture Notes in Computer Science
publication_identifier:
  isbn:
  - '9783031945748'
  - '9783031945755'
  issn:
  - 0302-9743
  - 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: Robustness Evaluation of Knowledge Graph Embedding Models Under Non-targeted
  Attacks
type: conference
user_id: '67199'
year: '2025'
...
---
_id: '63573'
author:
- first_name: Adel
  full_name: Memariani, Adel
  last_name: Memariani
- first_name: Michael
  full_name: Röder, Michael
  id: '67199'
  last_name: Röder
  orcid: https://orcid.org/0000-0002-8609-8277
- first_name: Arnab
  full_name: Sharma, Arnab
  id: '67200'
  last_name: Sharma
- 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: 'Memariani A, Röder M, Sharma A, Demir C, Ngonga Ngomo A-C. Link Prediction
    Under Non-targeted Attacks: Do Soft Labels Always Help? In: <i>Lecture Notes in
    Computer Science</i>. Springer Nature Switzerland; 2025. doi:<a href="https://doi.org/10.1007/978-3-032-09527-5_6">10.1007/978-3-032-09527-5_6</a>'
  apa: 'Memariani, A., Röder, M., Sharma, A., Demir, C., &#38; Ngonga Ngomo, A.-C.
    (2025). Link Prediction Under Non-targeted Attacks: Do Soft Labels Always Help?
    <i>Lecture Notes in Computer Science</i>. <a href="https://doi.org/10.1007/978-3-032-09527-5_6">https://doi.org/10.1007/978-3-032-09527-5_6</a>'
  bibtex: '@inproceedings{Memariani_Röder_Sharma_Demir_Ngonga Ngomo_2025, place={Cham},
    title={Link Prediction Under Non-targeted Attacks: Do Soft Labels Always Help?},
    DOI={<a href="https://doi.org/10.1007/978-3-032-09527-5_6">10.1007/978-3-032-09527-5_6</a>},
    booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland},
    author={Memariani, Adel and Röder, Michael and Sharma, Arnab and Demir, Caglar
    and Ngonga Ngomo, Axel-Cyrille}, year={2025} }'
  chicago: 'Memariani, Adel, Michael Röder, Arnab Sharma, Caglar Demir, and Axel-Cyrille
    Ngonga Ngomo. “Link Prediction Under Non-Targeted Attacks: Do Soft Labels Always
    Help?” In <i>Lecture Notes in Computer Science</i>. Cham: Springer Nature Switzerland,
    2025. <a href="https://doi.org/10.1007/978-3-032-09527-5_6">https://doi.org/10.1007/978-3-032-09527-5_6</a>.'
  ieee: 'A. Memariani, M. Röder, A. Sharma, C. Demir, and A.-C. Ngonga Ngomo, “Link
    Prediction Under Non-targeted Attacks: Do Soft Labels Always Help?,” 2025, doi:
    <a href="https://doi.org/10.1007/978-3-032-09527-5_6">10.1007/978-3-032-09527-5_6</a>.'
  mla: 'Memariani, Adel, et al. “Link Prediction Under Non-Targeted Attacks: Do Soft
    Labels Always Help?” <i>Lecture Notes in Computer Science</i>, Springer Nature
    Switzerland, 2025, doi:<a href="https://doi.org/10.1007/978-3-032-09527-5_6">10.1007/978-3-032-09527-5_6</a>.'
  short: 'A. Memariani, M. Röder, A. Sharma, C. Demir, A.-C. Ngonga Ngomo, in: Lecture
    Notes in Computer Science, Springer Nature Switzerland, Cham, 2025.'
date_created: 2026-01-12T17:18:35Z
date_updated: 2026-01-12T17:24:46Z
department:
- _id: '574'
- _id: '923'
doi: 10.1007/978-3-032-09527-5_6
language:
- iso: eng
place: Cham
publication: Lecture Notes in Computer Science
publication_identifier:
  isbn:
  - '9783032095268'
  - '9783032095275'
  issn:
  - 0302-9743
  - 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: 'Link Prediction Under Non-targeted Attacks: Do Soft Labels Always Help?'
type: conference
user_id: '67199'
year: '2025'
...
---
_id: '65734'
author:
- first_name: Louis Mozart
  full_name: Kamdem Teyou, Louis Mozart
  id: '101165'
  last_name: Kamdem Teyou
- first_name: Luke
  full_name: Friedrichs, Luke
  last_name: Friedrichs
- 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: Yasir
  full_name: Mahmood, Yasir
  id: '99353'
  last_name: Mahmood
- first_name: Stefan
  full_name: Heindorf, Stefan
  id: '11871'
  last_name: Heindorf
  orcid: 0000-0002-4525-6865
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  id: '65716'
  last_name: Ngonga Ngomo
citation:
  ama: 'Kamdem Teyou LM, Friedrichs L, Kouagou NJ, et al. Neural Reasoning for Robust
    Instance Retrieval in SHOIQ. In: ; 2025. doi:<a href="https://doi.org/10.1145/3731443.377134">https://doi.org/10.1145/3731443.377134</a>'
  apa: Kamdem Teyou, L. M., Friedrichs, L., Kouagou, N. J., Demir, C., Mahmood, Y.,
    Heindorf, S., &#38; Ngonga Ngomo, A.-C. (2025). <i>Neural Reasoning for Robust
    Instance Retrieval in SHOIQ</i>. The 13th COnference on Knowledge Capture (K-CAP’25),
    Dayton-USA. <a href="https://doi.org/10.1145/3731443.377134">https://doi.org/10.1145/3731443.377134</a>
  bibtex: '@inproceedings{Kamdem Teyou_Friedrichs_Kouagou_Demir_Mahmood_Heindorf_Ngonga
    Ngomo_2025, title={Neural Reasoning for Robust Instance Retrieval in SHOIQ}, DOI={<a
    href="https://doi.org/10.1145/3731443.377134">https://doi.org/10.1145/3731443.377134</a>},
    author={Kamdem Teyou, Louis Mozart and Friedrichs, Luke and Kouagou, N’Dah Jean
    and Demir, Caglar and Mahmood, Yasir and Heindorf, Stefan and Ngonga Ngomo, Axel-Cyrille},
    year={2025} }'
  chicago: Kamdem Teyou, Louis Mozart, Luke Friedrichs, N’Dah Jean Kouagou, Caglar
    Demir, Yasir Mahmood, Stefan Heindorf, and Axel-Cyrille Ngonga Ngomo. “Neural
    Reasoning for Robust Instance Retrieval in SHOIQ,” 2025. <a href="https://doi.org/10.1145/3731443.377134">https://doi.org/10.1145/3731443.377134</a>.
  ieee: 'L. M. Kamdem Teyou <i>et al.</i>, “Neural Reasoning for Robust Instance Retrieval
    in SHOIQ,” presented at the The 13th COnference on Knowledge Capture (K-CAP’25),
    Dayton-USA, 2025, doi: <a href="https://doi.org/10.1145/3731443.377134">https://doi.org/10.1145/3731443.377134</a>.'
  mla: Kamdem Teyou, Louis Mozart, et al. <i>Neural Reasoning for Robust Instance
    Retrieval in SHOIQ</i>. 2025, doi:<a href="https://doi.org/10.1145/3731443.377134">https://doi.org/10.1145/3731443.377134</a>.
  short: 'L.M. Kamdem Teyou, L. Friedrichs, N.J. Kouagou, C. Demir, Y. Mahmood, S.
    Heindorf, A.-C. Ngonga Ngomo, in: 2025.'
conference:
  end_date: 2025-12-12
  location: Dayton-USA
  name: The 13th COnference on Knowledge Capture (K-CAP'25)
  start_date: 2025-12-09
date_created: 2026-05-29T14:12:43Z
date_updated: 2026-05-29T14:16:06Z
department:
- _id: '574'
doi: https://doi.org/10.1145/3731443.377134
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://dl.acm.org/doi/10.1145/3731443.3771348
oa: '1'
status: public
title: Neural Reasoning for Robust Instance Retrieval in SHOIQ
type: conference
user_id: '101165'
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: <i>Companion Proceedings of the ACM on Web Conference 2024</i>. ACM; 2024.
    doi:<a href="https://doi.org/10.1145/3589335.3651978">10.1145/3589335.3651978</a>'
  apa: KOUAGOU, N. J., Demir, C., Zahera, H. M. A., Wilke, A., Heindorf, S., Li, J.,
    &#38; Ngonga Ngomo, A.-C. (2024). Universal Knowledge Graph Embeddings. <i>Companion
    Proceedings of the ACM on Web Conference 2024</i>. Companion Proceedings of the
    ACM on Web Conference 2024, Singapore. <a href="https://doi.org/10.1145/3589335.3651978">https://doi.org/10.1145/3589335.3651978</a>
  bibtex: '@inproceedings{KOUAGOU_Demir_Zahera_Wilke_Heindorf_Li_Ngonga Ngomo_2024,
    title={Universal Knowledge Graph Embeddings}, DOI={<a href="https://doi.org/10.1145/3589335.3651978">10.1145/3589335.3651978</a>},
    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 <i>Companion Proceedings of the ACM on Web Conference 2024</i>.
    ACM, 2024. <a href="https://doi.org/10.1145/3589335.3651978">https://doi.org/10.1145/3589335.3651978</a>.
  ieee: 'N. J. KOUAGOU <i>et al.</i>, “Universal Knowledge Graph Embeddings,” presented
    at the Companion Proceedings of the ACM on Web Conference 2024, Singapore, 2024,
    doi: <a href="https://doi.org/10.1145/3589335.3651978">10.1145/3589335.3651978</a>.'
  mla: KOUAGOU, N’Dah Jean, et al. “Universal Knowledge Graph Embeddings.” <i>Companion
    Proceedings of the ACM on Web Conference 2024</i>, ACM, 2024, doi:<a href="https://doi.org/10.1145/3589335.3651978">10.1145/3589335.3651978</a>.
  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: '58049'
abstract:
- lang: eng
  text: In recent years, knowledge graph embedding models have been successfully applied
    in the transductive setting to tackle various challenging tasks including link
    prediction, and query answering. Yet, the transductive setting does not allow
    for reasoning over unseen entities, relations, let alone numerical or non-numerical
    literals. Although increasing efforts are put into exploring inductive scenarios,
    inference over unseen entities, relations, and literals has yet to come. This
    limitation prohibits the existing methods from handling real-world dynamic knowledge
    graphs involving heterogeneous information about the world. Here, we propose a
    remedy to this limitation. We propose the attentive byte-pair encoding layer (BytE)
    to construct a triple embedding from a sequence of byte-pair encoded subword units
    of entities and relations. Compared to the conventional setting, BytE leads to
    massive feature reuse via weight tying, since it forces a knowledge graph embedding
    model to learn embeddings for subword units instead of entities and relations
    directly. Consequently, the size of the embedding matrices are not anymore bound
    to the unique number of entities and relations of a knowledge graph. Experimental
    results show that BytE improves the link prediction performance of 4 knowledge
    graph embedding models on datasets where the syntactic representations of triples
    are semantically meaningful. However, benefits of training a knowledge graph embedding
    model with BytE dissipate on knowledge graphs where entities and relations are
    represented with plain numbers or URIs. We provide an open source implementation
    of BytE to foster reproducible research.
author:
- 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: Arnab
  full_name: Sharma, Arnab
  id: '67200'
  last_name: Sharma
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  id: '65716'
  last_name: Ngonga Ngomo
citation:
  ama: Demir C, KOUAGOU NJ, Sharma A, Ngonga Ngomo A-C. Inference over Unseen Entities,
    Relations and Literals on Knowledge Graphs. <i>Arxiv</i>. Published online 2024.
    doi:<a href="https://doi.org/10.48550/ARXIV.2410.06742">10.48550/ARXIV.2410.06742</a>
  apa: Demir, C., KOUAGOU, N. J., Sharma, A., &#38; Ngonga Ngomo, A.-C. (2024). Inference
    over Unseen Entities, Relations and Literals on Knowledge Graphs. <i>Arxiv</i>.
    <a href="https://doi.org/10.48550/ARXIV.2410.06742">https://doi.org/10.48550/ARXIV.2410.06742</a>
  bibtex: '@article{Demir_KOUAGOU_Sharma_Ngonga Ngomo_2024, title={Inference over
    Unseen Entities, Relations and Literals on Knowledge Graphs}, DOI={<a href="https://doi.org/10.48550/ARXIV.2410.06742">10.48550/ARXIV.2410.06742</a>},
    journal={Arxiv}, author={Demir, Caglar and KOUAGOU, N’Dah Jean and Sharma, Arnab
    and Ngonga Ngomo, Axel-Cyrille}, year={2024} }'
  chicago: Demir, Caglar, N’Dah Jean KOUAGOU, Arnab Sharma, and Axel-Cyrille Ngonga
    Ngomo. “Inference over Unseen Entities, Relations and Literals on Knowledge Graphs.”
    <i>Arxiv</i>, 2024. <a href="https://doi.org/10.48550/ARXIV.2410.06742">https://doi.org/10.48550/ARXIV.2410.06742</a>.
  ieee: 'C. Demir, N. J. KOUAGOU, A. Sharma, and A.-C. Ngonga Ngomo, “Inference over
    Unseen Entities, Relations and Literals on Knowledge Graphs,” <i>Arxiv</i>, 2024,
    doi: <a href="https://doi.org/10.48550/ARXIV.2410.06742">10.48550/ARXIV.2410.06742</a>.'
  mla: Demir, Caglar, et al. “Inference over Unseen Entities, Relations and Literals
    on Knowledge Graphs.” <i>Arxiv</i>, 2024, doi:<a href="https://doi.org/10.48550/ARXIV.2410.06742">10.48550/ARXIV.2410.06742</a>.
  short: C. Demir, N.J. KOUAGOU, A. Sharma, A.-C. Ngonga Ngomo, Arxiv (2024).
date_created: 2025-01-06T12:19:39Z
date_updated: 2025-01-07T20:01:36Z
doi: 10.48550/ARXIV.2410.06742
language:
- iso: eng
publication: Arxiv
status: public
title: Inference over Unseen Entities, Relations and Literals on Knowledge Graphs
type: journal_article
user_id: '67200'
year: '2024'
...
---
_id: '58051'
author:
- first_name: Caglar
  full_name: Demir, Caglar
  id: '43817'
  last_name: Demir
- first_name: Arnab
  full_name: Sharma, Arnab
  id: '67200'
  last_name: Sharma
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  id: '65716'
  last_name: Ngonga Ngomo
citation:
  ama: Demir C, Sharma A, Ngonga Ngomo A-C. Adaptive Stochastic Weight Averaging.
    <i>arxiv</i>. Published online 2024. doi:<a href="https://doi.org/10.48550/ARXIV.2406.19092">10.48550/ARXIV.2406.19092</a>
  apa: Demir, C., Sharma, A., &#38; Ngonga Ngomo, A.-C. (2024). Adaptive Stochastic
    Weight Averaging. <i>Arxiv</i>. <a href="https://doi.org/10.48550/ARXIV.2406.19092">https://doi.org/10.48550/ARXIV.2406.19092</a>
  bibtex: '@article{Demir_Sharma_Ngonga Ngomo_2024, title={Adaptive Stochastic Weight
    Averaging}, DOI={<a href="https://doi.org/10.48550/ARXIV.2406.19092">10.48550/ARXIV.2406.19092</a>},
    journal={arxiv}, author={Demir, Caglar and Sharma, Arnab and Ngonga Ngomo, Axel-Cyrille},
    year={2024} }'
  chicago: Demir, Caglar, Arnab Sharma, and Axel-Cyrille Ngonga Ngomo. “Adaptive Stochastic
    Weight Averaging.” <i>Arxiv</i>, 2024. <a href="https://doi.org/10.48550/ARXIV.2406.19092">https://doi.org/10.48550/ARXIV.2406.19092</a>.
  ieee: 'C. Demir, A. Sharma, and A.-C. Ngonga Ngomo, “Adaptive Stochastic Weight
    Averaging,” <i>arxiv</i>, 2024, doi: <a href="https://doi.org/10.48550/ARXIV.2406.19092">10.48550/ARXIV.2406.19092</a>.'
  mla: Demir, Caglar, et al. “Adaptive Stochastic Weight Averaging.” <i>Arxiv</i>,
    2024, doi:<a href="https://doi.org/10.48550/ARXIV.2406.19092">10.48550/ARXIV.2406.19092</a>.
  short: C. Demir, A. Sharma, A.-C. Ngonga Ngomo, Arxiv (2024).
date_created: 2025-01-06T12:20:24Z
date_updated: 2025-01-07T20:00:53Z
doi: 10.48550/ARXIV.2406.19092
language:
- iso: eng
publication: arxiv
status: public
title: Adaptive Stochastic Weight Averaging
type: journal_article
user_id: '67200'
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: <i>Proceedings of
    the Thirty-ThirdInternational Joint Conference on Artificial Intelligence</i>.
    International Joint Conferences on Artificial Intelligence Organization; 2024.
    doi:<a href="https://doi.org/10.24963/ijcai.2024/479">10.24963/ijcai.2024/479</a>'
  apa: 'KOUAGOU, N. J., Heindorf, S., Demir, C., &#38; Ngonga Ngomo, A.-C. (2024).
    ROCES: Robust Class Expression Synthesis in Description Logics via Iterative Sampling.
    <i>Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial
    Intelligence</i>. <a href="https://doi.org/10.24963/ijcai.2024/479">https://doi.org/10.24963/ijcai.2024/479</a>'
  bibtex: '@inproceedings{KOUAGOU_Heindorf_Demir_Ngonga Ngomo_2024, title={ROCES:
    Robust Class Expression Synthesis in Description Logics via Iterative Sampling},
    DOI={<a href="https://doi.org/10.24963/ijcai.2024/479">10.24963/ijcai.2024/479</a>},
    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 <i>Proceedings of the Thirty-ThirdInternational Joint Conference
    on Artificial Intelligence</i>. International Joint Conferences on Artificial
    Intelligence Organization, 2024. <a href="https://doi.org/10.24963/ijcai.2024/479">https://doi.org/10.24963/ijcai.2024/479</a>.'
  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: <a href="https://doi.org/10.24963/ijcai.2024/479">10.24963/ijcai.2024/479</a>.'
  mla: 'KOUAGOU, N’Dah Jean, et al. “ROCES: Robust Class Expression Synthesis in Description
    Logics via Iterative Sampling.” <i>Proceedings of the Thirty-ThirdInternational
    Joint Conference on Artificial Intelligence</i>, International Joint Conferences
    on Artificial Intelligence Organization, 2024, doi:<a href="https://doi.org/10.24963/ijcai.2024/479">10.24963/ijcai.2024/479</a>.'
  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: '62702'
abstract:
- lang: eng
  text: '<jats:p>Clifford algebras are a natural extension of division algebras, including
    real numbers, complex numbers, quaternions, and octonions. Previous research in
    knowledge graph embeddings has focused exclusively on Clifford algebras of a specific
    type, which do not include nilpotent base vectors—elements that square to zero.
    In this work, we introduce a novel approach by incorporating nilpotent base vectors
    with a nilpotency index of two, leading to a more general form of Clifford algebras
    named degenerate Clifford algebras. This generalization to degenerate Clifford
    algebras does allow for covering dual numbers and as such include translations
    and rotations models under the same generalization paradigm for the first time.
    We develop two models to determine the parameters that define the algebra: one
    using a greedy search and another predicting the parameters based on neural network
    embeddings of the input knowledge graph. Our evaluation on seven benchmark datasets
    demonstrates that this incorporation of nilpotent vectors enhances the quality
    of embeddings. Additionally, our method outperforms state-of-the-art approaches
    in terms of generalization, particularly regarding the mean reciprocal rank achieved
    on validation data. Finally, we show that even a simple greedy search can effectively
    discover optimal or near-optimal parameters for the algebra.</jats:p>'
author:
- first_name: Louis Mozart
  full_name: Kamdem Teyou, Louis Mozart
  id: '101165'
  last_name: Kamdem Teyou
- 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: 'Kamdem Teyou LM, Demir C, Ngonga Ngomo A-C. Embedding Knowledge Graphs in
    Degenerate Clifford Algebras. In: <i>Frontiers in Artificial Intelligence and
    Applications</i>. IOS Press; 2024. doi:<a href="https://doi.org/10.3233/faia240627">10.3233/faia240627</a>'
  apa: Kamdem Teyou, L. M., Demir, C., &#38; Ngonga Ngomo, A.-C. (2024). Embedding
    Knowledge Graphs in Degenerate Clifford Algebras. In <i>Frontiers in Artificial
    Intelligence and Applications</i>. 27TH EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE,
    Santiago de Compostela. IOS Press. <a href="https://doi.org/10.3233/faia240627">https://doi.org/10.3233/faia240627</a>
  bibtex: '@inbook{Kamdem Teyou_Demir_Ngonga Ngomo_2024, title={Embedding Knowledge
    Graphs in Degenerate Clifford Algebras}, DOI={<a href="https://doi.org/10.3233/faia240627">10.3233/faia240627</a>},
    booktitle={Frontiers in Artificial Intelligence and Applications}, publisher={IOS
    Press}, author={Kamdem Teyou, Louis Mozart and Demir, Caglar and Ngonga Ngomo,
    Axel-Cyrille}, year={2024} }'
  chicago: Kamdem Teyou, Louis Mozart, Caglar Demir, and Axel-Cyrille Ngonga Ngomo.
    “Embedding Knowledge Graphs in Degenerate Clifford Algebras.” In <i>Frontiers
    in Artificial Intelligence and Applications</i>. IOS Press, 2024. <a href="https://doi.org/10.3233/faia240627">https://doi.org/10.3233/faia240627</a>.
  ieee: L. M. Kamdem Teyou, C. Demir, and A.-C. Ngonga Ngomo, “Embedding Knowledge
    Graphs in Degenerate Clifford Algebras,” in <i>Frontiers in Artificial Intelligence
    and Applications</i>, IOS Press, 2024.
  mla: Kamdem Teyou, Louis Mozart, et al. “Embedding Knowledge Graphs in Degenerate
    Clifford Algebras.” <i>Frontiers in Artificial Intelligence and Applications</i>,
    IOS Press, 2024, doi:<a href="https://doi.org/10.3233/faia240627">10.3233/faia240627</a>.
  short: 'L.M. Kamdem Teyou, C. Demir, A.-C. Ngonga Ngomo, in: Frontiers in Artificial
    Intelligence and Applications, IOS Press, 2024.'
conference:
  end_date: 2024-10-24
  location: Santiago de Compostela
  name: 27TH EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE
  start_date: 2024-10-19
date_created: 2025-11-28T14:32:43Z
date_updated: 2026-05-29T14:34:11Z
department:
- _id: '34'
- _id: '574'
doi: 10.3233/faia240627
language:
- iso: eng
popular_science: '1'
publication: Frontiers in Artificial Intelligence and Applications
publication_identifier:
  isbn:
  - '9781643685489'
  issn:
  - 0922-6389
  - 1879-8314
publication_status: published
publisher: IOS Press
quality_controlled: '1'
status: public
title: Embedding Knowledge Graphs in Degenerate Clifford Algebras
type: book_chapter
user_id: '101165'
year: '2024'
...
---
_id: '62703'
abstract:
- lang: eng
  text: We introduce a novel embedding method diverging from conventional approaches
    by operating within function spaces of finite dimension rather than finite vector
    space, thus departing significantly from standard knowledge graph embedding techniques.
    Initially employing polynomial functions to compute embeddings, we progress to
    more intricate representations using neural networks with varying layer complexities.
    We argue that employing functions for embedding computation enhances expressiveness
    and allows for more degrees of freedom, enabling operations such as composition,
    derivatives and primitive of entities representation. Additionally, we meticulously
    outline the step-by-step construction of our approach and provide code for reproducibility,
    thereby facilitating further exploration and application in the field.
author:
- first_name: Louis Mozart
  full_name: Kamdem Teyou, Louis Mozart
  id: '101165'
  last_name: Kamdem Teyou
- first_name: Caglar
  full_name: Demir, Caglar
  id: '43817'
  last_name: Demir
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  last_name: Ngonga Ngomo
citation:
  ama: 'Kamdem Teyou LM, Demir C, Ngonga Ngomo A-C. Embedding Knowledge Graphs in
    Function Spaces. In: <i>Proceedings of the 33rd ACM International Conference on
    Information and Knowledge Management</i>. ACM; 2024. doi:<a href="https://doi.org/10.1145/3627673.3679819">10.1145/3627673.3679819</a>'
  apa: Kamdem Teyou, L. M., Demir, C., &#38; Ngonga Ngomo, A.-C. (2024). Embedding
    Knowledge Graphs in Function Spaces. <i>Proceedings of the 33rd ACM International
    Conference on Information and Knowledge Management</i>. 33rd ACM International
    Conference on Information and Knowledge Management, Boise. <a href="https://doi.org/10.1145/3627673.3679819">https://doi.org/10.1145/3627673.3679819</a>
  bibtex: '@inproceedings{Kamdem Teyou_Demir_Ngonga Ngomo_2024, place={Boise}, title={Embedding
    Knowledge Graphs in Function Spaces}, DOI={<a href="https://doi.org/10.1145/3627673.3679819">10.1145/3627673.3679819</a>},
    booktitle={Proceedings of the 33rd ACM International Conference on Information
    and Knowledge Management}, publisher={ACM}, author={Kamdem Teyou, Louis Mozart
    and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2024} }'
  chicago: 'Kamdem Teyou, Louis Mozart, Caglar Demir, and Axel-Cyrille Ngonga Ngomo.
    “Embedding Knowledge Graphs in Function Spaces.” In <i>Proceedings of the 33rd
    ACM International Conference on Information and Knowledge Management</i>. Boise:
    ACM, 2024. <a href="https://doi.org/10.1145/3627673.3679819">https://doi.org/10.1145/3627673.3679819</a>.'
  ieee: 'L. M. Kamdem Teyou, C. Demir, and A.-C. Ngonga Ngomo, “Embedding Knowledge
    Graphs in Function Spaces,” presented at the 33rd ACM International Conference
    on Information and Knowledge Management, Boise, 2024, doi: <a href="https://doi.org/10.1145/3627673.3679819">10.1145/3627673.3679819</a>.'
  mla: Kamdem Teyou, Louis Mozart, et al. “Embedding Knowledge Graphs in Function
    Spaces.” <i>Proceedings of the 33rd ACM International Conference on Information
    and Knowledge Management</i>, ACM, 2024, doi:<a href="https://doi.org/10.1145/3627673.3679819">10.1145/3627673.3679819</a>.
  short: 'L.M. Kamdem Teyou, C. Demir, A.-C. Ngonga Ngomo, in: Proceedings of the
    33rd ACM International Conference on Information and Knowledge Management, ACM,
    Boise, 2024.'
conference:
  end_date: 2024-10-25
  location: Boise
  name: 33rd ACM International Conference on Information and Knowledge Management
  start_date: 2024-10-21
date_created: 2025-11-28T14:42:32Z
date_updated: 2026-05-29T14:32:04Z
department:
- _id: '34'
- _id: '574'
doi: 10.1145/3627673.3679819
language:
- iso: eng
place: Boise
publication: Proceedings of the 33rd ACM International Conference on Information and
  Knowledge Management
publication_status: published
publisher: ACM
status: public
title: Embedding Knowledge Graphs in Function Spaces
type: conference
user_id: '101165'
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: <i>Compendium of Neurosymbolic
    Artificial Intelligence</i>. IOS Press; 2023:272–286.'
  apa: Ngonga Ngomo, A.-C., Demir, C., Kouagou, N. J., Heindorf, S., Karalis, N.,
    &#38; Bigerl, A. (2023). Class Expression Learning with Multiple Representations.
    In <i>Compendium of Neurosymbolic Artificial Intelligence</i> (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 <i>Compendium of Neurosymbolic Artificial Intelligence</i>,
    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 <i>Compendium
    of Neurosymbolic Artificial Intelligence</i>, IOS Press, 2023, pp. 272–286.
  mla: Ngonga Ngomo, Axel-Cyrille, et al. “Class Expression Learning with Multiple
    Representations.” <i>Compendium of Neurosymbolic Artificial Intelligence</i>,
    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. <i>ECML PKDD</i>.
    Published online 2023.'
  apa: 'Demir, C., Wiebesiek, M., Lu, R., Ngonga Ngomo, A.-C., &#38; Heindorf, S.
    (2023). LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric
    Literals. <i>ECML PKDD</i>. 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.” <i>ECML PKDD</i>, 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,” <i>ECML
    PKDD</i>, 2023.'
  mla: 'Demir, Caglar, et al. “LitCQD: Multi-Hop Reasoning in Incomplete Knowledge
    Graphs with Numeric Literals.” <i>ECML PKDD</i>, 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: <i>Machine Learning and Knowledge Discovery in Databases:
    Research Track</i>. Springer Nature Switzerland; 2023. doi:<a href="https://doi.org/10.1007/978-3-031-43421-1_12">10.1007/978-3-031-43421-1_12</a>'
  apa: 'Kouagou, N. J., Heindorf, S., Demir, C., &#38; Ngonga Ngomo, A.-C. (2023).
    Neural Class Expression Synthesis in ALCHIQ(D). In <i>Machine Learning and Knowledge
    Discovery in Databases: Research Track</i>. European Conference on Machine Learning
    and Principles and Practice of Knowledge Discovery in Databases, Turin. Springer
    Nature Switzerland. <a href="https://doi.org/10.1007/978-3-031-43421-1_12">https://doi.org/10.1007/978-3-031-43421-1_12</a>'
  bibtex: '@inbook{Kouagou_Heindorf_Demir_Ngonga Ngomo_2023, place={Cham}, title={Neural
    Class Expression Synthesis in ALCHIQ(D)}, DOI={<a href="https://doi.org/10.1007/978-3-031-43421-1_12">10.1007/978-3-031-43421-1_12</a>},
    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 <i>Machine Learning
    and Knowledge Discovery in Databases: Research Track</i>. Cham: Springer Nature
    Switzerland, 2023. <a href="https://doi.org/10.1007/978-3-031-43421-1_12">https://doi.org/10.1007/978-3-031-43421-1_12</a>.'
  ieee: 'N. J. Kouagou, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Neural Class
    Expression Synthesis in ALCHIQ(D),” in <i>Machine Learning and Knowledge Discovery
    in Databases: Research Track</i>, Cham: Springer Nature Switzerland, 2023.'
  mla: 'Kouagou, N’Dah Jean, et al. “Neural Class Expression Synthesis in ALCHIQ(D).”
    <i>Machine Learning and Knowledge Discovery in Databases: Research Track</i>,
    Springer Nature Switzerland, 2023, doi:<a href="https://doi.org/10.1007/978-3-031-43421-1_12">10.1007/978-3-031-43421-1_12</a>.'
  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: '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: <i>NeSy 2023, 17th International Workshop on
    Neural-Symbolic Learning and Reasoning, Certosa Di Pontignano, Siena, Italy</i>.
    CEUR-WS; 2023.'
  apa: KOUAGOU, N. J., Heindorf, S., Demir, C., &#38; Ngonga Ngomo, A.-C. (2023).
    Neural Class Expression Synthesis (Extended Abstract). <i>NeSy 2023, 17th International
    Workshop on Neural-Symbolic Learning and Reasoning, Certosa Di Pontignano, Siena,
    Italy</i>.
  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 <i>NeSy 2023,
    17th International Workshop on Neural-Symbolic Learning and Reasoning, Certosa
    Di Pontignano, Siena, Italy</i>. 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).”
    <i>NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning,
    Certosa Di Pontignano, Siena, Italy</i>, 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: '54615'
author:
- 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: 'Demir C, Ngonga Ngomo A-C. Learning Permutation-Invariant Embeddings for Description
    Logic Concepts. In: <i>Advances in Intelligent Data Analysis XXI: 21st International
    Symposium on Intelligent Data Analysis, IDA 2023, Louvain-La-Neuve, Belgium, April
    12–14, 2023, Proceedings</i>. ; 2023:103–115.'
  apa: 'Demir, C., &#38; Ngonga Ngomo, A.-C. (2023). Learning Permutation-Invariant
    Embeddings for Description Logic Concepts. <i>Advances in Intelligent Data Analysis
    XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-La-Neuve,
    Belgium, April 12–14, 2023, Proceedings</i>, 103–115.'
  bibtex: '@inproceedings{Demir_Ngonga Ngomo_2023, title={Learning Permutation-Invariant
    Embeddings for Description Logic Concepts}, booktitle={Advances in Intelligent
    Data Analysis XXI: 21st International Symposium on Intelligent Data Analysis,
    IDA 2023, Louvain-la-Neuve, Belgium, April 12–14, 2023, Proceedings}, author={Demir,
    Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2023}, pages={103–115} }'
  chicago: 'Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “Learning Permutation-Invariant
    Embeddings for Description Logic Concepts.” In <i>Advances in Intelligent Data
    Analysis XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023,
    Louvain-La-Neuve, Belgium, April 12–14, 2023, Proceedings</i>, 103–115, 2023.'
  ieee: 'C. Demir and A.-C. Ngonga Ngomo, “Learning Permutation-Invariant Embeddings
    for Description Logic Concepts,” in <i>Advances in Intelligent Data Analysis XXI:
    21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve,
    Belgium, April 12–14, 2023, Proceedings</i>, 2023, pp. 103–115.'
  mla: 'Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “Learning Permutation-Invariant
    Embeddings for Description Logic Concepts.” <i>Advances in Intelligent Data Analysis
    XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-La-Neuve,
    Belgium, April 12–14, 2023, Proceedings</i>, 2023, pp. 103–115.'
  short: 'C. Demir, A.-C. Ngonga Ngomo, in: Advances in Intelligent Data Analysis
    XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-La-Neuve,
    Belgium, April 12–14, 2023, Proceedings, 2023, pp. 103–115.'
date_created: 2024-06-04T15:58:48Z
date_updated: 2024-06-04T15:59:04Z
department:
- _id: '574'
keyword:
- 318 SFB-TRR demir dice enexa ngonga sail
language:
- iso: eng
page: 103–115
publication: 'Advances in Intelligent Data Analysis XXI: 21st International Symposium
  on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12–14,
  2023, Proceedings'
status: public
title: Learning Permutation-Invariant Embeddings for Description Logic Concepts
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. <i>The Semantic
    Web - 20th Extended Semantic Web Conference (ESWC 2023)</i>. Vol 13870. Springer
    International Publishing; 2023:209-226. doi:<a href="https://doi.org/10.1007/978-3-031-33455-9_13">https://doi.org/10.1007/978-3-031-33455-9_13</a>'
  apa: KOUAGOU, N. J., Heindorf, S., Demir, C., &#38; 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, &#38; S. Hertling (Eds.), <i>The Semantic
    Web - 20th Extended Semantic Web Conference (ESWC 2023)</i> (Vol. 13870, pp. 209–226).
    Springer International Publishing. <a href="https://doi.org/10.1007/978-3-031-33455-9_13">https://doi.org/10.1007/978-3-031-33455-9_13</a>
  bibtex: '@inproceedings{KOUAGOU_Heindorf_Demir_Ngonga Ngomo_2023, title={Neural
    Class Expression Synthesis}, volume={13870}, DOI={<a href="https://doi.org/10.1007/978-3-031-33455-9_13">https://doi.org/10.1007/978-3-031-33455-9_13</a>},
    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 <i>The Semantic Web - 20th Extended
    Semantic Web Conference (ESWC 2023)</i>, 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. <a href="https://doi.org/10.1007/978-3-031-33455-9_13">https://doi.org/10.1007/978-3-031-33455-9_13</a>.
  ieee: 'N. J. KOUAGOU, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Neural Class
    Expression Synthesis,” in <i>The Semantic Web - 20th Extended Semantic Web Conference
    (ESWC 2023)</i>, Hersonissos, Crete, Greece, 2023, vol. 13870, pp. 209–226, doi:
    <a href="https://doi.org/10.1007/978-3-031-33455-9_13">https://doi.org/10.1007/978-3-031-33455-9_13</a>.'
  mla: KOUAGOU, N’Dah Jean, et al. “Neural Class Expression Synthesis.” <i>The Semantic
    Web - 20th Extended Semantic Web Conference (ESWC 2023)</i>, edited by Catia Pesquita
    et al., vol. 13870, Springer International Publishing, 2023, pp. 209–26, doi:<a
    href="https://doi.org/10.1007/978-3-031-33455-9_13">https://doi.org/10.1007/978-3-031-33455-9_13</a>.
  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: '46243'
author:
- first_name: Caglar
  full_name: Demir, Caglar
  id: '43817'
  last_name: Demir
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  last_name: Ngonga Ngomo
citation:
  ama: Demir C, Ngonga Ngomo A-C. Clifford Embeddings – A Generalized Approach for
    Embedding in Normed Algebras. <i>ECML-PKDD</i>. Published online 2023.
  apa: Demir, C., &#38; Ngonga Ngomo, A.-C. (2023). Clifford Embeddings – A Generalized
    Approach for Embedding in Normed Algebras. <i>ECML-PKDD</i>. European Conference
    on Machine Learning and Principles and Practice of Knowledge Discovery in Databases,
    Torino.
  bibtex: '@article{Demir_Ngonga Ngomo_2023, title={Clifford Embeddings – A Generalized
    Approach for Embedding in Normed Algebras}, journal={ECML-PKDD}, author={Demir,
    Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2023} }'
  chicago: Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “Clifford Embeddings – A
    Generalized Approach for Embedding in Normed Algebras.” <i>ECML-PKDD</i>, 2023.
  ieee: C. Demir and A.-C. Ngonga Ngomo, “Clifford Embeddings – A Generalized Approach
    for Embedding in Normed Algebras,” <i>ECML-PKDD</i>, 2023.
  mla: Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “Clifford Embeddings – A Generalized
    Approach for Embedding in Normed Algebras.” <i>ECML-PKDD</i>, 2023.
  short: C. Demir, A.-C. Ngonga Ngomo, ECML-PKDD (2023).
conference:
  location: Torino
  name: European Conference on Machine Learning and Principles and Practice of Knowledge
    Discovery in Databases
date_created: 2023-08-01T09:12:06Z
date_updated: 2023-08-01T09:22:40Z
ddc:
- '000'
file:
- access_level: open_access
  content_type: application/pdf
  creator: cdemir
  date_created: 2023-08-01T09:11:59Z
  date_updated: 2023-08-01T09:11:59Z
  file_id: '46244'
  file_name: public.pdf
  file_size: 408352
  relation: main_file
file_date_updated: 2023-08-01T09:11:59Z
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'
  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: Clifford Embeddings – A Generalized Approach for Embedding in Normed Algebras
type: journal_article
user_id: '43817'
year: '2023'
...
---
_id: '46251'
author:
- first_name: Caglar
  full_name: Demir, Caglar
  id: '43817'
  last_name: Demir
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  last_name: Ngonga Ngomo
citation:
  ama: Demir C, Ngonga Ngomo A-C. Neuro-Symbolic Class Expression Learning. <i>International
    Joint Conference on Artificial Intelligence</i>. Published online 2023.
  apa: Demir, C., &#38; Ngonga Ngomo, A.-C. (2023). Neuro-Symbolic Class Expression
    Learning. <i>International Joint Conference on Artificial Intelligence</i>. International
    Joint Conference on Artificial Intelligence IJCAI 2023, Macau.
  bibtex: '@article{Demir_Ngonga Ngomo_2023, title={Neuro-Symbolic Class Expression
    Learning}, journal={International Joint Conference on Artificial Intelligence},
    author={Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2023} }'
  chicago: Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “Neuro-Symbolic Class Expression
    Learning.” <i>International Joint Conference on Artificial Intelligence</i>, 2023.
  ieee: C. Demir and A.-C. Ngonga Ngomo, “Neuro-Symbolic Class Expression Learning,”
    <i>International Joint Conference on Artificial Intelligence</i>, 2023.
  mla: Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “Neuro-Symbolic Class Expression
    Learning.” <i>International Joint Conference on Artificial Intelligence</i>, 2023.
  short: C. Demir, A.-C. Ngonga Ngomo, International Joint Conference on Artificial
    Intelligence (2023).
conference:
  location: Macau
  name: International Joint Conference on Artificial Intelligence IJCAI 2023
date_created: 2023-08-01T09:30:37Z
date_updated: 2023-08-01T09:44:30Z
ddc:
- '000'
department:
- _id: '574'
file:
- access_level: open_access
  content_type: application/pdf
  creator: cdemir
  date_created: 2023-08-01T09:30:35Z
  date_updated: 2023-08-01T09:30:35Z
  file_id: '46252'
  file_name: public.pdf
  file_size: 340865
  relation: main_file
file_date_updated: 2023-08-01T09:30:35Z
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'
  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: International Joint Conference on Artificial Intelligence
status: public
title: Neuro-Symbolic Class Expression Learning
type: journal_article
user_id: '43817'
year: '2023'
...
---
_id: '31545'
abstract:
- lang: eng
  text: Knowledge graph embedding research has mainly focused on learning continuous
    representations of entities and relations tailored towards the link prediction
    problem. Recent results indicate an ever increasing predictive ability of current
    approaches on benchmark datasets. However, this effectiveness often comes with
    the cost of over-parameterization and increased computationally complexity. The
    former induces extensive hyperparameter optimization to mitigate malicious overfitting.
    The latter magnifies the importance of winning the hardware lottery. Here, we
    investigate a remedy for the first problem. We propose a technique based on Kronecker
    decomposition to reduce the number of parameters in a knowledge graph embedding
    model, while retaining its expressiveness. Through Kronecker decomposition, large
    embedding matrices are split into smaller embedding matrices during the training
    process. Hence, embeddings of knowledge graphs are not plainly retrieved but reconstructed
    on the fly. The decomposition ensures that elementwise interactions between three
    embedding vectors are extended with interactions within each embedding vector.
    This implicitly reduces redundancy in embedding vectors and encourages feature
    reuse. To quantify the impact of applying Kronecker decomposition on embedding
    matrices, we conduct a series of experiments on benchmark datasets. Our experiments
    suggest that applying Kronecker decomposition on embedding matrices leads to an
    improved parameter efficiency on all benchmark datasets. Moreover, empirical evidence
    suggests that reconstructed embeddings entail robustness against noise in the
    input knowledge graph. To foster reproducible research, we provide an open-source
    implementation of our approach, including training and evaluation scripts as well
    as pre-trained models in our knowledge graph embedding framework.
author:
- first_name: Caglar
  full_name: Demir, Caglar
  id: '43817'
  last_name: Demir
- first_name: Julian
  full_name: Lienen, Julian
  id: '44040'
  last_name: Lienen
- first_name: Axel-Cyrille
  full_name: Ngonga Ngomo, Axel-Cyrille
  id: '65716'
  last_name: Ngonga Ngomo
citation:
  ama: Demir C, Lienen J, Ngonga Ngomo A-C. Kronecker Decomposition for Knowledge
    Graph Embeddings. <i>arXiv:220506560</i>. Published online 2022.
  apa: Demir, C., Lienen, J., &#38; Ngonga Ngomo, A.-C. (2022). Kronecker Decomposition
    for Knowledge Graph Embeddings. In <i>arXiv:2205.06560</i>.
  bibtex: '@article{Demir_Lienen_Ngonga Ngomo_2022, title={Kronecker Decomposition
    for Knowledge Graph Embeddings}, journal={arXiv:2205.06560}, author={Demir, Caglar
    and Lienen, Julian and Ngonga Ngomo, Axel-Cyrille}, year={2022} }'
  chicago: Demir, Caglar, Julian Lienen, and Axel-Cyrille Ngonga Ngomo. “Kronecker
    Decomposition for Knowledge Graph Embeddings.” <i>ArXiv:2205.06560</i>, 2022.
  ieee: C. Demir, J. Lienen, and A.-C. Ngonga Ngomo, “Kronecker Decomposition for
    Knowledge Graph Embeddings,” <i>arXiv:2205.06560</i>. 2022.
  mla: Demir, Caglar, et al. “Kronecker Decomposition for Knowledge Graph Embeddings.”
    <i>ArXiv:2205.06560</i>, 2022.
  short: C. Demir, J. Lienen, A.-C. Ngonga Ngomo, ArXiv:2205.06560 (2022).
date_created: 2022-05-31T07:04:36Z
date_updated: 2022-05-31T07:05:50Z
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/2205.06560
oa: '1'
publication: arXiv:2205.06560
status: public
title: Kronecker Decomposition for Knowledge Graph Embeddings
type: preprint
user_id: '44040'
year: '2022'
...
---
_id: '31546'
abstract:
- lang: eng
  text: In semi-supervised learning, the paradigm of self-training refers to the idea
    of learning from pseudo-labels suggested by the learner itself. Across various
    domains, corresponding methods have proven effective and achieve state-of-the-art
    performance. However, pseudo-labels typically stem from ad-hoc heuristics, relying
    on the quality of the predictions though without guaranteeing their validity.
    One such method, so-called credal self-supervised learning, maintains pseudo-supervision
    in the form of sets of (instead of single) probability distributions over labels,
    thereby allowing for a flexible yet uncertainty-aware labeling. Again, however,
    there is no justification beyond empirical effectiveness. To address this deficiency,
    we make use of conformal prediction, an approach that comes with guarantees on
    the validity of set-valued predictions. As a result, the construction of credal
    sets of labels is supported by a rigorous theoretical foundation, leading to better
    calibrated and less error-prone supervision for unlabeled data. Along with this,
    we present effective algorithms for learning from credal self-supervision. An
    empirical study demonstrates excellent calibration properties of the pseudo-supervision,
    as well as the competitiveness of our method on several benchmark datasets.
author:
- first_name: Julian
  full_name: Lienen, Julian
  id: '44040'
  last_name: Lienen
- first_name: Caglar
  full_name: Demir, Caglar
  id: '43817'
  last_name: Demir
- first_name: Eyke
  full_name: Hüllermeier, Eyke
  id: '48129'
  last_name: Hüllermeier
citation:
  ama: Lienen J, Demir C, Hüllermeier E. Conformal Credal Self-Supervised Learning.
    <i>arXiv:220515239</i>. Published online 2022.
  apa: Lienen, J., Demir, C., &#38; Hüllermeier, E. (2022). Conformal Credal Self-Supervised
    Learning. In <i>arXiv:2205.15239</i>.
  bibtex: '@article{Lienen_Demir_Hüllermeier_2022, title={Conformal Credal Self-Supervised
    Learning}, journal={arXiv:2205.15239}, author={Lienen, Julian and Demir, Caglar
    and Hüllermeier, Eyke}, year={2022} }'
  chicago: Lienen, Julian, Caglar Demir, and Eyke Hüllermeier. “Conformal Credal Self-Supervised
    Learning.” <i>ArXiv:2205.15239</i>, 2022.
  ieee: J. Lienen, C. Demir, and E. Hüllermeier, “Conformal Credal Self-Supervised
    Learning,” <i>arXiv:2205.15239</i>. 2022.
  mla: Lienen, Julian, et al. “Conformal Credal Self-Supervised Learning.” <i>ArXiv:2205.15239</i>,
    2022.
  short: J. Lienen, C. Demir, E. Hüllermeier, ArXiv:2205.15239 (2022).
date_created: 2022-05-31T07:05:36Z
date_updated: 2022-05-31T07:05:54Z
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/2205.15239
oa: '1'
publication: arXiv:2205.15239
status: public
title: Conformal Credal Self-Supervised Learning
type: preprint
user_id: '44040'
year: '2022'
...