Publications - Data Science Junior Research Group

Universal Knowledge Graph Embeddings

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.

DOI

Utilizing Description Logics for Global Explanations of Heterogeneous Graph Neural Networks

D. Köhler, S. Heindorf, ArXiv:2405.12654 (2024).

arXiv

Causal Question Answering with Reinforcement Learning

L. Blübaum, S. Heindorf, in: The World Wide Web Conference (WWW), ACM, n.d., pp. 2204–2215.

DOI

Beyond One-Shot Explanations: A Systematic Literature Review of Dialogue-Based XAI Approaches

D. Mindlin, F. Beer, L.N. Sieger, S. Heindorf, P. Cimiano, E. Esposito, A.-C. Ngonga Ngomo, (2024).

EDGE: Evaluation Framework for Logical vs. Subgraph Explanations for Node Classifiers on Knowledge Graphs

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.

DOI

AutoCL: AutoML for Concept Learning

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.

DOI

Class Expression Learning with Multiple Representations

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.

LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals

C. Demir, M. Wiebesiek, R. Lu, A.-C. Ngonga Ngomo, S. Heindorf, ECML PKDD (2023).

PDF

Neural Class Expression Synthesis in ALCHIQ(D)

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.

DOI PDF

Explaining ELH Concept Descriptions through Counterfactual Reasoning

L.N. Sieger, S. Heindorf, L. Blübaum, A.-C. Ngonga Ngomo, ArXiv:2301.05109 (2023).

arXiv

Neural Class Expression Synthesis (Extended Abstract)

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.

Neural Class Expression Synthesis

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.

DOI

Accelerating Concept Learning via Sampling

A. Baci, S. Heindorf, in: CIKM, 2023, pp. 3733–3737.

DOI PDF

AI-Based Assistance System for Manufacturing

S. Deppe, L. Brandt, M. Brünninghaus, J. Papenkordt, S. Heindorf, G. Tschirner-Vinke, (2022).

DOI https://ieeexplore.ieee.org/document/9921520

Learning Concept Lengths Accelerates Concept Learning in ALC

N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: The Semantic Web, Springer International Publishing, Cham, 2022.

DOI https://link.springer.com/chapter/10.1007/978-3-031-06981-9_14

EvoLearner: Learning Description Logics with Evolutionary Algorithms

S. Heindorf, L. Blübaum, N. Düsterhus, T. Werner, V.N. Golani, C. Demir, A.-C. Ngonga Ngomo, in: WWW, ACM, 2022, pp. 818–828.

DOI

CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications

S. Pestryakova, D. Vollmers, M. Sherif, S. Heindorf, M. Saleem, D. Moussallem, A.-C. Ngonga Ngomo, Scientific Data (2022).

DOI

User Involvement in Training Smart Home Agents

L.N. Sieger, J. Hermann, A. Schomäcker, S. Heindorf, C. Meske, C.-C. Hey, A. Doğangün, in: International Conference on Human-Agent Interaction, ACM, 2022.

DOI

Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings

H.M.A. Zahera, S. Heindorf, S. Balke, J. Haupt, M. Voigt, C. Walter, F. Witter, A.-C. Ngonga Ngomo, in: The Semantic Web: ESWC 2022 Satellite Events, Springer International Publishing, Cham, 2022.

DOI

CausalQA: A Benchmark for Causal Question Answering

A. Bondarenko, M. Wolska, S. Heindorf, L. Blübaum, A.-C. Ngonga Ngomo, B. Stein, P. Braslavski, M. Hagen, M. Potthast, in: Proceedings of the 29th International Conference on Computational Linguistics, International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 2022, pp. 3296–3308.

Drift Detection in Text Data with Document Embeddings

R. Feldhans, A. Wilke, S. Heindorf, M.H. Shaker, B. Hammer, A.-C. Ngonga Ngomo, E. Hüllermeier, in: Intelligent Data Engineering and Automated Learning – IDEAL 2021, Springer International Publishing, Cham, 2021.

DOI https://link.springer.com/chapter/10.1007/978-3-030-91608-4_11

Convolutional Hypercomplex Embeddings for Link Prediction

C. Demir, D. Moussallem, S. Heindorf, A.-C. Ngonga Ngomo, in: The 13th Asian Conference on Machine Learning, ACML 2021, 2021.

arXiv

Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts

T. Nickchen, S. Heindorf, G. Engels, in: 2021 IEEE Winter Conference on Applications of Computer Vision (WACV), IEEE, 2021.

DOI

Automatically generating instructions from tutorials for search and user navigation

S. Heindorf, (2021).

ASSET: A Semi-supervised Approach for Entity Typing in Knowledge Graphs

H.M.A. Zahera, S. Heindorf, A.-C. Ngonga Ngomo, in: Proceedings of the 11th on Knowledge Capture Conference, ACM, 2021.

DOI

CauseNet: Towards a Causality Graph Extracted from the Web

S. Heindorf, Y. Scholten, H. Wachsmuth, A.-C. Ngonga Ngomo, M. Potthast, in: Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2020), 2020, pp. 3023–3030.

DOI

Debiasing Vandalism Detection Models at Wikidata

S. Heindorf, Y. Scholten, G. Engels, M. Potthast, in: WWW, ACM, 2019, pp. 670–680.

DOI

Vandalism Detection in Crowdsourced Knowledge Bases

S. Heindorf, Vandalism Detection in Crowdsourced Knowledge Bases, Universität Paderborn, 2019.

Debiasing Vandalism Detection Models at Wikidata (Extended Abstract)

S. Heindorf, Y. Scholten, G. Engels, M. Potthast, in: INFORMATIK, 2019, pp. 289–290.

DOI

Semantic Data Mediator: Linking Services to Websites

D. Wolters, S. Heindorf, J. Kirchhoff, G. Engels, in: L. Braubach, J.M. Murillo, N. Kaviani, M. Lama, L. Burgueño, N. Moha, M. Oriol (Eds.), Service-Oriented Computing -- ICSOC 2017 Workshops, Springer International Publishing, Cham, 2018, pp. 388–392.

DOI

Linking Services to Websites by Leveraging Semantic Data

D. Wolters, S. Heindorf, J. Kirchhoff, G. Engels, in: I. Altintas, S. Chen (Eds.), 2017 IEEE International Conference on Web Services (ICWS), IEEE, 2017.

DOI

Overview of the Wikidata Vandalism Detection Task at WSDM Cup 2017

S. Heindorf, M. Potthast, G. Engels, B. Stein, in: WSDM Cup 2017 Notebook Papers, 2017.

Proceedings of the WSDM Cup 2017: Vandalism Detection and Triple Scoring

M. Potthast, S. Heindorf, H. Bast, ArXiv:1712.09528 (2017).

arXiv

WSDM Cup 2017: Vandalism Detection and Triple Scoring

S. Heindorf, M. Potthast, H. Bast, B. Buchhold, E. Haussmann, in: WSDM, ACM, 2017, pp. 827–828.

DOI

Vandalism Detection in Wikidata

S. Heindorf, M. Potthast, B. Stein, G. Engels, in: Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM 2016), 2016, pp. 327--336.

DOI

Towards Vandalism Detection in Knowledge Bases

S. Heindorf, M. Potthast, B. Stein, G. Engels, in: SIGIR, ACM, 2015, pp. 831–834.

DOI

Optimized XPath evaluation for Schema-compressed XML data

S. Böttcher, R. Hartel, S. Heindorf, in: ADC, Australian Computer Society, 2012, pp. 137–144.