Situation-specific Development of Business Models within Software Ecosystems
S. Gottschalk, Situation-Specific Development of Business Models within Software Ecosystems, Paderborn University, Paderborn, 2022.

MultPAX: Keyphrase Extraction Using Language Models and Knowledge Graphs
H.M. Zahera, D. Vollmers, M.A. Sherif, A.-C. Ngonga Ngomo, in: U. Sattler, A. Hogan, C.M. Keet, V. Presutti, J.P.A. Almeida, H. Takeda, P. Monnin, G. Pirrò, C. d’Amato (Eds.), The Semantic Web - ISWC 2022 - 21st International Semantic Web Conference, Virtual Event, October 23-27, 2022, Proceedings, Springer, 2022, pp. 303–318.

Can Machine Translation be a Reasonable Alternative for Multilingual Question Answering Systems over Knowledge Graphs?
A. Perevalov, A. Both, D. Diefenbach, A.-C. Ngonga Ngomo, in: F. Laforest, R. Troncy, E. Simperl, D. Agarwal, A. Gionis, I. Herman, L. Médini (Eds.), WWW ’22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25 - 29, 2022, ACM, 2022, pp. 977–986.

Proceedings of the QuWeDa 2022: 6th Workshop on Storing, Querying and Benchmarking Knowledge Graphs co-located with 21st International Semantic Web Conference (ISWC 2022), Hangzhou, China, 23-27 October 2022
M. Saleem, A.-C. Ngonga Ngomo, DE, eds., Proceedings of the QuWeDa 2022: 6th Workshop on Storing, Querying and Benchmarking Knowledge Graphs Co-Located with 21st International Semantic Web Conference (ISWC 2022), Hangzhou, China, 23-27 October 2022, CEUR-WS.org, 2022.

Hashing the Hypertrie: Space- and Time-Efficient Indexing for SPARQL in Tensors
A. Bigerl, L. Conrads, C. Behning, M. Saleem, A.-C. Ngonga Ngomo, in: U. Sattler, A. Hogan, C.M. Keet, V. Presutti, J.P.A. Almeida, H. Takeda, P. Monnin, G. Pirrò, C. d’Amato (Eds.), The Semantic Web - ISWC 2022 - 21st International Semantic Web Conference, Virtual Event, October 23-27, 2022, Proceedings, Springer, 2022, pp. 57–73.

REBench: Microbenchmarking Framework for Relation Extraction Systems
M. Ali, M. Saleem, A.-C. Ngonga Ngomo, in: U. Sattler, A. Hogan, C.M. Keet, V. Presutti, J.P.A. Almeida, H. Takeda, P. Monnin, G. Pirrò, C. d’Amato (Eds.), The Semantic Web - ISWC 2022 - 21st International Semantic Web Conference, Virtual Event, October 23-27, 2022, Proceedings, Springer, 2022, pp. 643–659.

Rapid Explainability for Skill Description Learning
C. Demir, A. Himmelhuber, Y. Liu, A. Bigerl, D. Moussallem, A.-C. Ngonga Ngomo, in: A. Dimou, A. Haller, A.L. Gentile, P. Ristoski (Eds.), Proceedings of the ISWC 2022 Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice Co-Located with 21st International Semantic Web Conference (ISWC 2022), Virtual Conference, Hangzhou, China, October 23-27, 2022, CEUR-WS.org, 2022.

LSQ Framework: The LSQ Framework for SPARQL Query Log Processing
C. Stadler, M. Saleem, A.-C. Ngonga Ngomo, in: M. Saleem, A.-C.N. Ngomo (Eds.), Proceedings of the QuWeDa 2022: 6th Workshop on Storing, Querying and Benchmarking Knowledge Graphs Co-Located with 21st International Semantic Web Conference (ISWC 2022), Hangzhou, China, 23-27 October 2022, CEUR-WS.org, 2022, pp. 49–64.

Kronecker Decomposition for Knowledge Graph Embeddings
C. Demir, J. Lienen, A.-C. Ngonga Ngomo, in: A. Bellogín, L. Boratto, F. Cena (Eds.), HT ’22: 33rd ACM Conference on Hypertext and Social Media, Barcelona, Spain, 28 June 2022- 1 July 2022, ACM, 2022, pp. 1–10.

Enhancing the Accessibility of Knowledge Graph Question Answering Systems through Multilingualization
A. Perevalov, A.-C. Ngonga Ngomo, A. Both, in: 16th IEEE International Conference on Semantic Computing, ICSC 2022, Laguna Hills, CA, USA, January 26-28, 2022, IEEE, 2022, pp. 251–256.

TaOnto: Unsupervised Semantification with Knowledge Graph Embeddings
H.M. Zahera, S. Heindorf, S. Balke, J. Haupt, M. Voigt, C. Walter, F. Witter, A.-C. Ngonga Ngomo, in: P. Groth, A. Rula, J. Schneider, I. Tiddi, E. Simperl, P. Alexopoulos, R. Hoekstra, M. Alam, A. Dimou, M. Tamper (Eds.), The Semantic Web: ESWC 2022 Satellite Events - Hersonissos, Crete, Greece, May 29 - June 2, 2022, Proceedings, Springer, 2022, pp. 47–51.

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: N. Calzolari, C.-R. Huang, H. Kim, J. Pustejovsky, L. Wanner, K.-S. Choi, P.-M. Ryu, H.-H. Chen, L. Donatelli, H. Ji, S. Kurohashi, P. Paggio, N. Xue, S. Kim, Y. Hahm, Z. He, T.K. Lee, E. Santus, F. Bond, S.-H. Na (Eds.), Proceedings of the 29th International Conference on Computational Linguistics, COLING 2022, Gyeongju, Republic of Korea, October 12-17, 2022, International Committee on Computational Linguistics, 2022, pp. 3296–3308.

Knowledge Graphs
A. Hogan, E. Blomqvist, M. Cochez, C. d’Amato, G. de Melo, C. Gutierrez, S. Kirrane, J.E.L. Gayo, R. Navigli, S. Neumaier, A.-C. Ngonga Ngomo, A. Polleres, S.M. Rashid, A. Rula, L. Schmelzeisen, J.F. Sequeda, S. Staab, A. Zimmermann, ACM Comput. Surv. 54 (2022) 71:1–71:37.

A survey of RDF stores & SPARQL engines for querying knowledge graphs
W. Ali, M. Saleem, B. Yao, A. Hogan, A.-C. Ngonga Ngomo, VLDB J. 31 (2022) 1–26.

Hardware-agnostic computation for large-scale knowledge graph embeddings
C. Demir, A.-C. Ngonga Ngomo, Softw. Impacts 13 (2022) 100377.

Evaluating database systems relying on secure multiparty computation
A. Anonymous, Evaluating Database Systems Relying on Secure Multiparty Computation, 2022.

Cost of Privacy-preserving SMPC Protocols for NN-Based Inference
A. Anonymous, Cost of Privacy-Preserving SMPC Protocols for NN-Based Inference, 2022.

Lattice Revocation Mechanisms
J. Lohse, Lattice Revocation Mechanisms, 2022.

Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens
B. Hammer, E. Hüllermeier, V. Lohweg, A. Schneider, W. Schenck, U. Kuhl, M. Braun, A. Pfeifer, C.-A. Holst, M. Schmidt, G. Schomaker, T. Tornede, Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens, 2022.

A Comprehensive Study on Face Recognition Biases Beyond Demographics
P. Terhörst, J.N. Kolf, M. Huber, F. Kirchbuchner, N. Damer, A.M. Moreno, J. Fierrez, A. Kuijper, IEEE Transactions on Technology and Society 3 (2022) 16–30.