Publikationen des Instituts für Informatik und Wirtschaftsinformatik

2025

Brechlin, A., Schäfer, J. und Armknecht, F. (2025). Buy crypto, sell privacy: an extended investigation of the cryptocurrency exchange Evonax. International Journal of Network Management, 35, 1–16.
Brinkmann, A., Shraga, R. und Bizer, C. (2025). ExtractGPT: Exploring the potential of Large Language Models for product attribute value extraction. In , Information integration and web intelligence : 26th International Conference, iiWAS 2024, Bratislava, Slovak Republic, December 2–4, 2024, Proceedings. Part I (S. 38–52). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Gautam, D. und Kellmeyer, P. (2025). Exploring the credibility of large language models for mental health support: Protocol for a scoping review. JMIR Research Protocols, 14, 1–8.
Iana, A., Glavaš, G. und Paulheim, H. (2025). Peeling back the layers: An in-depth evaluation of encoder architectures in neural news recommenders. In , INRA 2024 : Proceedings of the International Workshop on News Recommendation and Analytics co-located with the 2024 ACM Conference on Recommender Systems (RecSys 2024) (S. 1–15). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Iana, A., Schmidt, F. D., Glavaš, G. und Paulheim, H. (2025). News without borders: Domain adaptation of multilingual sentence embeddings for cross-lingual news recommendation. In , Advances in Information Retrieval : 47th European Conference on Information Retrieval, ECIR 2025, Lucca, Italy, April 6–10, 2025, Proceedings, Part II (S. 119–137). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Kappenberger, J., Stuckenschmidt, H. und Gerdon, F. (2025). Pricing parking for fairness — A simulation study based on an empirically calibrated model of parking behavior. Transportation Research. Part A, Policy and Practice, 193, 1–29.
Kessel, M. und Atkinson, C. (2025). Morescient GAI for software engineering. ACM Transactions on SoftwareEngineering and Methodology : TOSEM, June 2024 (forthcoming).
Kessel, M. und Atkinson, C. (2025). N-version assessment and enhancement of generative AI : differential GAI. IEEE Software, 42, 76–83.
Kirchdorfer, L., Blümel, R., Kampik, T., der Aa, H. und Stuckenschmidt, H. (2025). Discovering multi-agent systems for resource-centric business process simulation. Process Science, 2, 1–26.
Klironomos, A. (2025). Towards democratized machine learning: a semantic web approach. In , Companion Proceedings of the ACM Web Conference 2025 : WWW companion'25 (S. 697–700). , Association for Computing Machinery: New York, NY.
Kochsiek, A. (2025). Neural methods for link prediction in knowledge graphs. Dissertation. Mannheim.
Korini, K. und Bizer, C. (2025). Column property annotation using large language models. In , The Semantic Web: ESWC 2024 Satellite Events : Hersonissos, Crete, Greece, May 26–30, 2024, Proceedings, Part I (S. 61–70). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Kretzer, F., Kolthoff, K., Bartelt, C., Ponzetto, S. P. und Maedche, A. (2025). Closing the loop between user stories and GUI prototypes: an LLM-based assistant for cross-functional integration in software development. In , CHI '25 : proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (S. 1–19). , Association for Computing Machinery: New York, NY, USA.
Mai, H. T., Cuong Xuan, C. und Paulheim, H. (2025). Do LLMs really adapt to domains? An ontology learning perspective. In , The Semantic Web – ISWC 2024 : 23rd International Semantic Web Conference, Baltimore, MD, USA, November 11–15, 2024, Proceedings. Part 1 (S. 126–143). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Marton, S., Grams, T., Vogt, F., Lüdtke, S., Bartelt, C. und Stuckenschmidt, H. (2025). Mitigating information loss in tree-based reinforcement learning via direct optimization. In , The Thirteens International Conference on Learning Representations (S. ). , OpenReview.net: .
Marton, S., Schneider, M., Brinkmann, J., Lüdtke, S., Bartelt, C. und Stuckenschmidt, H. (2025). Decision trees that remember: Gradient-based learning of recurrent decision trees with memory. In , The Thirteens International Conference on Learning Representations (S. ). , OpenReview.net: .
Paull, S., Bubak, A. und Stuckenschmidt, H. (2025). Machine learning for master production scheduling: combining probabilistic forecasting with stochastic optimisation. Expert Systems with Applications, 271, 1–13.
Peeters, R. (2025). Entity matching using deep neural networks: From discriminative pre-trained language models to generative large language models. Dissertation. Mannheim.
Peeters, R., Steiner, A. und Bizer, C. (2025). Entity matching using large language models. In , Proceedings 28th International Conference on Extending Database Technology (EDBT 2025), Barcelona, Spain, March 25-March 28 (S. 529–541). OpenProceedings, OpenProceedings.org: Konstanz.
Shaban, A. und Paulheim, H. (2025). SnapE – training snapshot ensembles of link prediction models. In , The Semantic Web – ISWC 2024 : 23rd International Semantic Web Conference, Baltimore, MD, USA, November 11–15, 2024, Proceedings. Part 1 (S. 3–22). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Sousa, R. T. und Paulheim, H. (2025). Gene expression knowledge graph for patient representation and diabetes prediction. Journal of Biomedical Semantics, 16, 1–16.
Sousa, R. T., Pesquita, C. und Paulheim, H. (2025). Towards leveraging explicit negative statements in knowledge graph embeddings. Journal of Web Semantics, 84, 1–6.

2024

Meroño Peñuela, A., Dimou, A., Troncy, R., Hartig, O., Acosta, M., Alam, M., Paulheim, H. und Lisena, P. (Hrsg.) (2024). The Semantic Web : 21st International Conference, ESWC 2024, Hersonissos, Crete, Greece, May 26–30, 2024, Proceedings. Part 1. Cham: Springer.
Meroño Peñuela, A., Dimou, A., Troncy, R., Hartig, O., Acosta, M., Alam, M., Paulheim, H. und Lisena, P. (Hrsg.) (2024). The Semantic Web : 21st International Conference, ESWC 2024, Hersonissos, Crete, Greece, May 26–30, 2024, Proceedings. Part 2. Cham: Springer.
Amiri Elyasi, K., Sola, D., Meilicke, C., der Aa, H. und Stuckenschmidt, H. (2024). Knowledge graph completion for activity recommendation in business process modeling. Künstliche Intelligenz : KI, 1–15.
Amiri Elyasi, K., van der Aa, H. und Stuckenschmidt, H. (2024). PGTNet: a process graph transformer network for remaining time prediction of business process instances. In , Advanced information systems egineering : 36th international conference, CAiSE 2024, Limassol, Cyprus, June 3–7, 2024 : proceedings (S. 124–140). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Armknecht, F. und Müller, C. (2024). Towards a cryptographic model for wireless communication. In , Proceedings of the 21st International Conference on Security and Cryptography – SECRYPT (S. 249–261). , SciTePress: Setúbal.
Atkinson, C., Kühne, T. und Lange, A. (2024). Misconceptions about potency-based deep instantiation. In , Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems, MODELS Companion 2024, Linz, Austria, September 22–27, 2024 (S. 810–817). , ACM: Linz.
Betz, P., Galarraga, L., Ott, S., Meilicke, C., Suchanek, F. M. und Stuckenschmidt, H. (2024). PyClause – Simple and efficient rule handling for knowledge graphs. In , Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence Demo Track : Jeju, 03–09 August 2024 (S. 1–3). tba, International Joint Conferences on Artificial Intelligence: Jeju, South Korea.
Betz, P., Lüdtke, S., Meilicke, C. und Stuckenschmidt, H. (2024). Rule Confidence Aggregation for Knowledge Graph Completion. In , Rules and reasoning : 8th International Joint Conferrence, RuleML+RR 2024, Rucharest, Romania, September 16–18, 2024, Proceedings (S. 1–1). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Bombieri, M., Rospocher, M., Ponzetto, S. P. und Fiorini, P. (2024). Surgicberta: a pre-trained language model for procedural surgical language. International Journal of Data Science and Analytics, 18, 69–81.
Bombieri, M., Rospocher, M., Ponzetto, S. P. und Fiorini, P. (2024). The robotic-surgery propositional bank. Language Resources and Evaluation, 58, 1043-1071.
Brinkmann, A., Baumann, N. und Bizer, C. (2024). Using LLMs for the extraction and normalization of product attribute values. In , Advances in databases and information systems : 28th European Conference, ADBIS 2024, Bayonne, France, August 28–31, 2024 ; Proceedings (S. 217–230). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Brinkmann, A., Shraga, R. und Bizer, C. (2024). SC-block: Supervised contrastive blocking within entity resolution pipelines. In , The Semantic Web : 21st International Conference, ESWC 2024, Hersonissos, Crete, Greece, May 26–30, 2024, Proceedings, Part I (S. 121–142). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Bubak, A., Rolf, B., Reggelin, T., Lang, S. und Stuckenschmidt, H. (2024). An LSTM network-based genetic algorithm for integrated procurement and scheduling optimisation. International Journal of Production Research, 1–30.
Böckling, M., Paulheim, H. und Detzler, S. (2024). A planet scale spatial-temporal knowledge graph based on OpenStreetMap and H3 grid. In , GeoLD 2024: Geospatial Linked Data Workshop 2024 : proceedings of the 6th International Workshop on Geospatial Linked Data 2024, co-located with 21st Extended Semantic Web Conference (ESWC 2024) : Hersonissos, Greece, May 26th, 2024 (S. 60–72). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Böckling, M., Paulheim, H. und Detzler, S. (2024). Comparing spatial-temporal knowledge graph on spatial downstream tasks. In , International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2024) : 32nd ACM SIGSPATIAL (S. 581–584). , Association for Computing Machinery: New York, NY.
Cohausz, L., Kappenberger, J. und Stuckenschmidt, H. (2024). Combining fairness and causal graphs to advance both. In , Fairness and Bias in AI : Proceedings of the 2nd Workshop on Fairness and Bias in AI, co-located with 27th European Conference on Artificial Intelligence (ECAI 2024) (S. 1–14). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Cohausz, L., Kappenberger, J. und Stuckenschmidt, H. (2024). What fairness metrics can really tell you: A case study in the educational domain. In , LAK'24: Proceedings of the 14th Learning Analytics and Knowledge Conference (S. 792–799). , Association for Computing Machinery: Kyoto, Japan.
Cohausz, L., Tschalzev, A., Bartelt, C. und Stuckenschmidt, H. (2024). Investigating demographic features and their connection to performance, predictions, and fairness in EDM models. Journal of Educational Data Mining, 16, 177–213.
Dieing, T. I., Scheffler, M. und Cohausz, L. (2024). Enhancing chatbot-assisted study program orientation. In , Workshopband der 22. Fachtagung Bildungstechnologien (DELFI) : 09.09.-11.09.2024, Fulda, Deutschland (S. 223–232). , Gesellschaft für Informatik (GI): Bonn.
Faria de Souza, V. und Paulheim, H. (2024). Towards binarization of knowledge graph embeddings for node classification. In , Proceedings of the ISWC 2024 Posters, Demos and Industry Tracks: from novel ideas to industrial practice co-located with 23rd International Semantic Web Conference (S. 1–6). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Gastinger, J., Meilicke, C., Errica, F., Sztyler, T., Schuelke, A. und Stuckenschmidt, H. (2024). History repeats itself: A Baseline for Temporal Knowledge Graph Forecasting. In , Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence Demo Track : Jeju, 03–09 August 2024 (S. ). , International Joint Conferences on Artificial Intelligence: Jeju, South Korea.
Heist, N. (2024). Exploiting semi-structured information in Wikipedia for knowledge graph construction. Dissertation. Mannheim.
Hertling, S. (2024). Knowledge graph : generation and integration at scale. Dissertation. Mannheim.
Hubert, N., Paulheim, H., Brun, A. und Monticolo, D. (2024). Do similar entities have similar embeddings? In , The Semantic Web : 21st International Conference, ESWC 2024, Hersonissos, Crete, Greece, May 26–30, 2024, Proceedings. Part I (S. 3–21). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Hung, C. (2024). Multidimensional adaptation of language models: domains, languages, and social dimensions. Dissertation. Mannheim.
Iana, A., Alam, M. und Paulheim, H. (2024). A survey on knowledge-aware news recommender systems. Semantic Web, 15, 21–82.
Iana, A., Glavaš, G. und Paulheim, H. (2024). MIND Your Language: A multilingual dataset for cross-lingual news recommendation (extended abstract). In , KI 2024: Advances in Artificial Intelligence : 47th German Conference on AI, Würzburg, Germany, September 25–2, 2024, proceedings (S. 335–340). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Iana, A., Glavaš, G. und Paulheim, H. (2024). MIND your language: A multilingual dataset for cross-lingual news recommendation. In , Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14–18, 2024 (S. 553–563). , ACM: New York.
Iana, A., Glavaš, G. und Paulheim, H. (2024). Train once, use flexibly: A modular framework for multi-aspect neural news recommendation. In , Findings of EMNLP 2024 : The 2024 Conference on Empirical Methods in Natural Language Processing : November 12–16, 2024 (S. 9555-9571). , Association for Computational Linguistics: Miami, Florida, USA.
Kadel, P., Heist, N., Paulheim, H. und Mata, J. (2024). From pixels to palate: Communication around #vegan on Instagram and its relation with eating intentions. Appetite : Multidisciplinary Research on Eating and Drinking, 200, 1–10.
Kappenberger, J. und Stuckenschmidt, H. (2024). A framework for human-centered AI-based public policies. In Human-centered AI: A multidisciplinary perspective for policy-makers, auditors, and users (S. 287–303). Boca Raton: CRC Press.
Keil, M. (2024). AI-supported UI design for enhanced development of neurodiverse-friendly IT-systems. In , NordDesign 2024. Proceedings (S. 1–10). , The Design Society: .
Kessel, M. und Atkinson, C. (2024). Code search engines for the next generation. The Journal of Systems and Software : JSS, 215, 1–25.
Kessel, M. und Atkinson, C. (2024). Promoting open science in test-driven software experiments. The Journal of Systems and Software : JSS, 212, 1–20.
Kirchdorfer, L., Blümel, R., Kampik, T., van der Aa, H. und Stuckenschmidt, H. (2024). AgentSimulator: an agent-based approach for data-driven business process simulation. In , 2024 6th International Conference on Process Mining : ICPM 2024 : Kgs. Lyngby, Denmark, 14–18 October 2024 : proceedings (S. 97–104). , IEEE: Piscataway, NJ.
Krause, F., Kurniawan, K., Kiesling, E., Martinez-Gil, J., Hoch, T., Pichler, M., Heinzl, B. und Moser, B. (2024). Leveraging semantic representations via knowledge graph embeddings. In Artificial intelligence in manufacturing : enabling intelligent, flexible and cost-effective production through AI (S. 71–85). Cham: Springer.
Krause, F., Paulheim, H., Kiesling, E., Kurniawan, K., Leva, M. C., Estrada-Lugo, H. D., Stübl, G., Üre, N. K., Dominguez-Ledo, J., Khan, M., Demolder, P., Gaux, H., Heinzl, B., Hoch, T., Martinez-Gil, J., Silvina, A. und Moser, B. A. (2024). Managing human-AI collaborations within Industry 5.0 scenarios via knowledge graphs: key challenges and lessons learned. Frontiers in Artificial Intelligence, 7, 1–20.
Litschko, R. (2024). Resource-lean transfer methods for cross-lingual information retrieval. Dissertation. Mannheim.
Marton, S., Lüdtke, S., Bartelt, C. und Stuckenschmidt, H. (2024). GRANDE: Gradient-Based Decision Tree Ensembles for tabular data. In , International Conference on Learning Representations (S. 1–27). , OpenReview.net: .
Marton, S., Lüdtke, S., Bartelt, C. und Stuckenschmidt, H. (2024). GradTree: Learning axis-aligned decision trees with gradient descent. In , Proceedings of the 38th AAAI Conference on Artificial Intelligence (S. 14323-14331). , AAAI Press: Washington, DC.
Marton, S., Lüdtke, S., Bartelt, C., Tschalzev, A. und Stuckenschmidt, H. (2024). Explaining neural networks without access to training data. Machine Learning, 113, 3633-3652.
Meilicke, C., Chekol, M. W., Betz, P., Fink, M. und Stuckenschmidt, H. (2024). Anytime bottom-up rule learning for large-scale knowledge graph completion. The VLDB Journal, 33, 131–161.
Moerkotte, G. (2024). Cardinality estimation for having-clauses. Proceedings of the VLDB Endowment, 18, 28–41.
Ott, S., Meilicke, C. und Stuckenschmidt, H. (2024). Reevaluation of inductive link prediction. In , Rules and reasoning : 8th international joint conference, RuleML+RR 2024, Bucharest, Romania, September 16–18, 2024 : proceedings (S. 75–90). Lecture notes in computer science, Springer: Cham.
Pandya, D. und Stuckenschmidt, H. (2024). Evaluating the impact of different acoustic contexts on German speech recognition. In , 2024 IEEE international conference on pervasive computing and communications workshops and other affiliated events (PerCom workshops) : 11–15 March 2024 in Biarritz, France (S. 1–5). , IEEE: Piscataway, NJ.
Peeters, R., Brinkmann, A. und Bizer, C. (2024). The Web Data Commons Schema.org Table Corpora. In , WWW '24 companion : companion proceedings of the ACM Web Conference 2024 (S. 1079-1082). , Association for Computing Machinery: New York, NY, United States.
Portisch, J. und Paulheim, H. (2024). The RDF2vec family of knowledge graph embedding methods : An experimental evaluation of RDF2vec variants and their capabilitie. Semantic Web, 15, 845–876.
Rehbein, I. und Ponzetto, S. P. (2024). A new resource and baselines for opinion role labelling in German parliamentary debates. In , ParlaCLARIN IV : workshop on Creatign, Analysing, and Increasing Accessibility of Parliamentary Corpora : LREC-COLING 2024 (S. 163–170). , ELRA: Torino, Italia.
Rehbein, I., Ruppenhofer, J., Brunner, A. und Ponzetto, S. P. (2024). Out of the mouths of MPs: Speaker attribution in parliamentary debates. In , The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) : main conference proceedings, 20–25 May, 2024, Torino, Italia (S. 12553-12563). , ELRA and ICCL: Torino, Italia.
Reinig, I., Becker, M., Rehbein, I. und Ponzetto, S. P. (2024). A survey on modelling morality for text analysis. In , Findings of the Association for Computational Linguistics ACL 2024, 62nd annual meeting of the Association for Computational Linguistics (ACL 2024) : Proceedings of the conference, August 11–16, 2024 (S. 4136-4155). , Association for Computational Linguistics (ACL): Kerrville, TX.
Reinig, I., Rehbein, I. und Ponzetto, S. P. (2024). How to do politics with words: Investigating speech acts in parliamentary debates. In , The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) : main conference proceedings, 20–25 May, 2024, Torino, Italia (S. 8287-8300). , ELRA and ICCL: Torino, Italia.
Scheffler, M., Dieing, T. I. und Cohausz, L. (2024). Developing a personalized study program recommender. In , Workshopband der 22. Fachtagung Bildungstechnologien (DELFI) : 9.-11. September 2024, Fulda, Deutschland (S. 233–240). , Gesellschaft für Informatik (GI): Bonn.
Schlechtinger, M. (2024). Investigating, predicting, and mitigating collusive behavior in deep reinforcement learning-based pricing AIs. Dissertation. Mannheim.
Schlechtinger, M., Kosack, D., Krause, F. und Paulheim, H. (2024). By fair means or foul: Quantifying collusion in a market simulation with deep reinforcement learning. In , Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI-24 : main track (S. 485–493). , International Joint Conferences on Artificial Intelligence Organization: Darmstadt ; Vienna.
Sousa, R. T. und Paulheim, H. (2024). Integrating heterogeneous gene expression data through knowledge graphs for improving diabetes prediction. In , SeWeBMeDa 2024 : Proceedings of the 7th Workshop on Semantic Web solutions for large-scale biomedical data analytics co-located with the ESWC 2024: Extended Semantic Web Conference (ESWC 2024) (S. 1–11). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Spreitzenbarth, J., Bode, C. und Stuckenschmidt, H. (2024). Artificial intelligence and machine learning in purchasing and supply management: A mixed-methods review of the state-of-the-art in literature and practice. Journal of Purchasing and Supply Management, 30, 1–21.
Takeshita, S., Green, T., Friedrich, N., Eckert, K. und Ponzetto, S. P. (2024). Cross-lingual extreme summarization of scholarly documents. International Journal on Digital Libraries, 25, 249–271.
Takeshita, S., Green, T., Reinig, I., Eckert, K. und Ponzetto, S. P. (2024). ACLSum: A new dataset for aspect-based summarization of scientific publications. In , The 2024 Conference of the North American Chapter of the Association for Computational Linguistics : proceedings of the conference, June 16–21, 2024. Volume 1 Long papers (S. 6660-6675). , Association for Computational Linguistics (ACL): Kerrville, TX.
Takeshita, S., Ponzetto, S. P. und Eckert, K. (2024). ROUGE-K: Do your summaries have keywords? In , The 13th Joint Conference on Lexical and Computational Semantics : proceedings of the Conference (*SEM 2024), June 20–21, 2024 (S. 69–79). , Association for Computational Linguistics (ACL): Stroudsburg, PA.
Tschalzev, A., Marton, S., Lüdtke, S., Bartelt, C. und Stuckenschmidt, H. (2024). A data-centric perspective on evaluating machine learning models for tabular data. In , The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track (S. 1–35). , NeurIPS: Vancouver, BC.
Tschalzev, A., Nitschke, P., Kirchdorfer, L., Lüdtke, S., Bartelt, C. und Stuckenschmidt, H. (2024). Enabling mixed effects neural networks for diverse, clustered data using Monte Carlo methods. In , Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence: Jeju, 03–09 August 2024 (S. ). , International Joint Conferences on Artificial Intelligence: Jeju, South Korea.
Weber, T., Ojha, M., Sadeghi, M., König, L., Armbruster, M., Lange, A., Burger, E. und Atkinson, C. (2024). Towards deep reactions in multi-level, multi-view modeling. In , MODELS 24: ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems: Companion proceedings : Linz, Austria, 22–27 september 2024 (S. 760–769). , Association for Computing Machinery: New York, NY.
Wilken, N., Cohausz, L., Bartelt, C. und Stuckenschmidt, H. (2024). Fact Probability Vector Based Goal Recognition. In , 27th European Conference on Artificial Intelligence, 19–24 October 2024, Santiago de Compostela, Spain – Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024) (S. 4254-4261). Frontiers in Artificial Intelligence and Applications, IOS Press: Amsterdam [u. a.].

2023

Abd Nikooie Pour, M., Algergawy, A., Buche, P., Castro, L. J., Chen, J., Coulet, A., Cufi, J., Dong, H., Fallatah, O., Faria, D., Fundulaki, I., Hertling, S., He, Y., Horrocks, I., Huschka, M., Ibanescu, L., Jain, S., Jiménez-Ruiz, E., Karam, N., Lambrix, P., Li, H., Li, Y., Monnin, P., Nasr, E., Paulheim, H., Pesquita, C., Saveta, T., Shvaiko, P., Sousa, G., Trojahn, C., Vataščinová, J., Wu, M., Yaman, B., Zamazal, O. und Zhou, L. (2023). Results of the Ontology Alignment Evaluation Initiative 2023. In , OM 2023: Ontology Matching : proceedings of the 18th International Workshop on Ontology Matching, co-located with the 22nd International Semantic Web Conference (ISWC 2023) : Athens, Greece, November 7, 2023 (S. 97–139). CEUR workshop proceedings, RWTH Aachen: Aachen, Germany.
Armknecht, F., Heng, Y. und Schnell, R. (2023). Strengthening privacy-preserving record linkage using diffusion. In , (S. 298–311). Proceedings on Privacy Enhancing Technologies : PoPETs, De Gruyter Open: Warsaw, Poland.
Baumgartner, M., Dell'Aglio, D., Paulheim, H. und Bernstein, A. (2023). Towards the web of embeddings: integrating multiple knowledge graph embedding spaces with FedCoder. Web Semantics, 75, 1–18.
Biswas, R., Kaffee, L.-A., Cochez, M. und Paulheim, H. (2023). Knowledge graph embeddings: open challenges and opportunities. Transactions on Graph Data and Knowledge : TGDK, 1, 1–32.
Bizer, C., Heath, T. und Berners-Lee, T. (2023). Linked data – the story so far. In Linking the world’s information: Essays on Tim Berners-Lee’s Invention of the World Wide Web (S. 115–143). New York: ACM Digital Library.
Bombieri, M., Rospocher, M., Ponzetto, S. P. und Fiorini, P. (2023). Machine understanding surgical actions from intervention procedure textbooks. Computers in Biology and Medicine, 152, 1–12.
Breit, A., Waltersdorfer, L., Ekaputra, F. J., Sabou, M., Ekelhart, A., Iana, A., Paulheim, H., Portisch, J., Revenko, A., Teije, A. . und van Harmelen, F. (2023). Combining machine learning and semantic web: A systematic mapping study. ACM Computing Surveys : CSUR, 55, 1–41.
Brinkmann, A. (2023). Neural data search for table augmentation. In , Proceedings of the Workshops of the EDBT/ICDT 2023 Joint Conference, Ioannina, Greece, March, 28, 2023 (S. 1–4). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Brinkmann, A., Primpeli, A. und Bizer, C. (2023). The Web Data Commons Schema.Org Data Set Series. In , The ACM Web Conference : Companion of the World Wide Web Conference WWW 2023 (S. 136–139). , Association for Computing Machinery: New York, NY.
Busch, K., Rochlitzer, A., Sola, D. und Leopold, H. (2023). Just tell me: Prompt engineering in business process management. In , Enterprise, business-process and information systems modeling : 24th International Conference, BPMDS 2023, and 28th International Conference, EMMSAD 2023, Zaragoza, Spain, June 12–13, 2023, proceedings (S. 3–11). Lecture Notes in Business Information Processing : LNBIP, Springer: Berlin [u. a.].
Böckling, M., Paulheim, H. und Detzler, S. (2023). Wildfire prediction for California using and comparing Spatio-Temporal Knowledge Graphs. Information Technology : IT, 65, 189–199.
Böckling, M., Paulheim, H. und Detzler, S. (2023). Wildfire prediction using spatio-temporal knowledge graphs. In , D2R2 2023: Proceedings of the Second International Workshop on Linked Data-driven Resilience Research 2023 co-located with Extended Semantic Web Conference 2023 (ESWC 2023) (S. 1–11). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Cohausz, L., Tschalzev, A., Bartelt, C. und Stuckenschmidt, H. (2023). Investigating the importance of demographic features for EDM-predictions. In , Proceedings of the 16th International Conference on Educational Data Mining (S. 125–136). , International Educational Data Mining Society: Bengaluru, India.
Daniel, R. (2023). Knowledge graph embeddings: link prediction and beyond. Dissertation. Mannheim.
De la Peña Sarracén, G. L., Rosso, P., Litschko, R., Glavaš, G. und Ponzetto, S. P. (2023). Vicinal risk minimization for few-shot cross-lingual transfer in abusive language detection. In , The 2023 Conference on Empirical Methods in Natural Language Processing : proceedings of the conference, December 6–10, 2023 (S. 4069-4085). , Association for Computational Linguistics (ACL): Stroudsburg, PA.
Ekaputra, F. J., Llugiqi, M., Sabou, M. und Paulheim, H. (2023). Describing and organizing semantic web and machine learning systems in the SWeMLS-KG. In , The semantic web : 20th International Conference, ESWC 2023, Hersonissos, Crete, Greece, May 28 – June 1, 2023 : proceedings (S. 372–389). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Fent, P., Moerkotte, G. und Neumann, T. (2023). Asymptotically better query optimization using indexed algebra. Proceedings of the VLDB Endowment, 16, 3018-3030.
Friede, D. (2023). Exploring discrete representations in stochastic computation graphs: Challenges, benefits, and novel strategies. Dissertation. Mannheim.
Friede, D., Reimers, C., Stuckenschmidt, H. und Niepert, M. (2023). Learning disentangled discrete representations. In , Machine learning and knowledge discovery in databases : research track : European conference, EMCL PKDD 2023, Turin, Italy, september 18–22,2023, proceedings, part IV (S. 593–609). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Gastinger, J., Sztyler, T., Sharma, L., Schuelke, A. und Stuckenschmidt, H. (2023). Comparing apples and oranges? : on the evaluation of methods for temporal knowledge graph forecasting. In , Machine learning and knowledge discovery in databases: research track : European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023 : proceedings. Part III (S. 533–549). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Gautschi, T., Gschwend, T., Oberländer, L., Ponzetto, S. P. und Stuckenschmidt, H. (2023). Der Mannheim Master in Social Data Science. In , INFORMATIK 2023 : Designing Futures: Zukünfte gestalten (S. 81–88). GI-Edition : Lecture Notes in Informatics. Proceedings, Gesellschaft für Informatik (GI): Bonn.
Green, T., Ponzetto, S. P. und Glavaš, G. (2023). Massively multilingual lexical specialization of multilingual transformers. In , The 61st Conference of the the Association for Computational Linguistics : July 9–14, 2023 : ACL 2023. (S. 7700-7715). , Association for Computational Linguistics, ACL: Stroudsburg, PA.
Hassanzadeh, O., Abdelmageed, N., Efthymiou, V., Chen, J., Cutrona, V., Hulsebos, M., Jiménez-Ruiz, E., Khatiwada, A., Korini, K., Kruit, B., Sequeda, J. und Srinivas, K. (2023). Results of SemTab 2023. In , Proceedings of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching, SemTab 2023, co-located with the 22nd International Semantic Web Conference, ISWC 2023, Athens, Greece, November 6–10, 2023 (S. 1–14). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
He, Y., Schreckenberger, C., Stuckenschmidt, H. und Wu, X. (2023). Towards utilitarian online learning – A review of online algorithms in open feature space. In , Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (S. 6647-6655). , International Joint Conferences on Artificial Intelligence Organization: Macao SAR.
Heist, N., Hertling, S. und Paulheim, H. (2023). KGrEaT: a framework to evaluate knowledge graphs via downstream tasks. In , CIKM '23 : Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (S. 3938-3942). , Association for Computing Machinery: New York, NY.
Heist, N. und Paulheim, H. (2023). NASTyLinker: NIL-aware scalable transformer-based entity linker. In , The Semantic Web : 20th International Conference, ESWC 2023, Hersonissos, Crete, Greece, May 28-June 1, 2023, Proceedings (S. 174–191). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Hertling, S. und Paulheim, H. (2023). OLaLa results for OAEI 2023. In , OM 2023: Ontology Matching : proceedings of the 18th International Workshop on Ontology Matching, co-located with the 22nd International Semantic Web Conference (ISWC 2023) : Athens, Greece, November 7, 2023 (S. 170–177). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Hertling, S. und Paulheim, H. (2023). OLaLa: Ontology matching with large language models. In , K-CAP ‘23 : proceedings of the 12th Knowledge Capture conference 2023, Pensacola, Florida, USA (S. 131–139). , Association for Computing Machinery: New York, NY.
Hertling, S. und Paulheim, H. (2023). Transformer based semantic relation typing for knowledge graph integration. In , The semantic web: 20th international conference, ESWC 2023 Hersonissos, Crete, Greece, May 28–June 1, 2023 : proceedings (S. 105–121). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Hubert, N., Paulheim, H., Monnin, P., Brun, A. und Monticolo, D. (2023). Schema first! Learn versatile knowledge graph embeddings by capturing semantics with MASCHInE. In , K-CAP ‘23: Proceedings of the 12th Knowledge Capture Conference 2023: Pensacola, Florida, USA (S. 188–196). , Association for Computing Machinery: New York, NY.
Hung, C.-C., Lauscher, A., Hovy, D., Ponzetto, S. P. und Glavaš, G. (2023). Can demographic factors improve text classification? Revisiting demographic adaptation in the age of transformers. In , The 17th Conference of the European Chapter of the Association for Computational Linguistics : Findings of EACL 2023, May 2–6, 2023 (S. 1565-1580). , Association for Computational Linguistics (ACL): Stroudsburg, PA.
Iana, A., Alam, M., Grote, A., Nikolajevic, N., Ludwig, K., Müller, P., Weinhardt, C. und Paulheim, H. (2023). NeMig – A bilingual news collection and knowledge graph about migration. In , Proceedings of the International Workshop on News Recommendation and Analytics co-located with the 2023 ACM Conference on Recommender Systems (RecSys 2023) (S. 1–22). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Iana, A., Glavaš, G. und Paulheim, H. (2023). NewsRecLib: A PyTorch-Lightning library for neural news recommendation. In , EMNLP 2023, The 2023 Conference on Empirical Methods in Natural Language Processing : proceedings of the system demonstrations (S. 296–310). , Association for Computational Linguistics, ACL: Stroudsburg, PA.
Iana, A., Glavaš, G. und Paulheim, H. (2023). Simplifying content-based neural news recommendation: On user modeling and training objectives. In , Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '23) (S. 2384-2388). , Association for Computing Machinery: New York, NY, United States.
Keil, M. V. und Bleisinger, O. (2023). Benutzeroberflächen von MBSE-Tools und deren Auswirkung auf neurodivergente Systemarchitekten. In , Tag des Systems Engineering (S. 9–15). , Books on Demand GmbH: Bremen.
Kessel, M. (2023). LASSO – an observatorium for the dynamic selection, analysis and comparison of software. Dissertation. Mannheim.
Klamm, C., Rehbein, I. und Ponzetto, S. P. (2023). Our kind of people? Detecting populist references in political debates. In , Findings of EACL 2023 : The 17th Conference of the European Chapter of the Association for Computational Linguistics (S. 1227-1243). , Association for Computational Linguistics: Dubrovnik, Croatia.
Klironomos, A., Zhou, B., Tan, Z., Zheng, Z., Mohamed, G.-E., Paulheim, H. und Kharlamov, E. (2023). ExeKGLib: knowledge graphs-empowered machine learning analytics. In , The semantic web: 20th international conference, ESWC 2023 Hersonissos, Crete, Greece, May 28–June 1, 2023 : proceedings (S. 123–127). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Kobbe, J. (2023). Automatic generation of structured explanations for arguments from consequences. Dissertation. Mannheim.
Kobbe, J., Hulpus, I. und Stuckenschmidt, H. (2023). Effect graph: Effect relation extraction for explanation generation. In , Proceedings of the 1st Workshop on Natural Language Reasoning and Structured Explanations (NLRSE) (S. 116–127). , Association for Computational Linguistics: Toronto, Canada.
Kochsiek, A. und Gemulla, R. (2023). A benchmark for semi-inductive link prediction in knowledge graphs. In , The 2023 Conference on Empirical Methods in Natural Language Processing – Findings of the Association for Computational Linguistics: EMNLP 2023, December 6–10, 2023 (S. 10634-10643). , Association for Computational Linguistics: Stroudsburg, PA.
Kochsiek, A., Niesel, F. und Gemulla, R. (2023). Start small, think big: On hyperparameter optimization for large-scale knowledge graph embeddings. In , Machine learning and knowledge discovery in databases : European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022 : proceedings. Part II (S. 138–154). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Kochsiek, A., Saxena, A., Nair, I. und Gemulla, R. (2023). Friendly neighbors: contextualized sequence-to-sequence link prediction. In , The 8th Workshop on Representation Learning for NLP (RepL4NLP 2023) : Proceedings of the workshop (S. 131–138). , Association for Computational Linguistics: Stroudsburg, PA.
Kolthoff, K., Bartelt, C. und Ponzetto, S. P. (2023). Correction to: Data-driven prototyping via natural- language-based GUI retrieval. Automated Software Engineering, 30, 1–2.
Kolthoff, K., Bartelt, C. und Ponzetto, S. P. (2023). Data-driven prototyping via natural-language-based GUI retrieval. Automated Software Engineering, 30, 1–34.
Korini, K. und Bizer, C. (2023). Column type annotation using ChatGPT. In , Joint proceedings of workshops at the 49th International Conference on Very Large Data Bases (VLDB 2023), Vancouver, Canada, August 28 – September 1, 2023, VLDBW 2023 (S. 1–12). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Krause, F., Kurniawan, K., Kiesling, E., Paulheim, H. und Polleres, A. (2023). On the representation of dynamic BPMN process executions in knowledge graphs. In , Knowledge graphs and semantic web : 5th Iberoamerican conference and 4th Indo-American conference, KGSWC 2023, Zaragoza, Spain, November 13–15, 2023 : proceedings (S. 97–105). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Lambert, M., Schuster, T., Kessel, M. und Atkinson, C. (2023). Robustness analysis of machine learning models using domain-specific test data perturbation. In , 22nd EPIA Conference on Artificial Intelligence, EPIA 2023, Faial Island, Azores, September 5–8, 2023, Proceedings. Part I. (S. 158–170). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Lange, A. (2023). Deep multi-style, multi-pattern modeling with DOCL. Dissertation. Mannheim.
Li, Y., Martschat, S. und Ponzetto, S. P. (2023). Multi-source (pre-)training for cross-domain measurement, unit and context extraction. In , BioNLP and BioNLP-ST : proceedings of the workshop : July 13, 2023 (S. 1–25). , Association for Computational Linguistics (ACL): Stroudsburg, PA.
Ludwig, K., Grote, A., Iana, A., Alam, M., Paulheim, H., Sack, H., Weinhardt, C. und Müller, P. (2023). Divided by the algorithm? The (limited) effects of content- and sentiment-based news recommendation on affective, ideological, and perceived polarization. Social Science Computer Review : SSCORE, 41, 2188-2210.
Lüdtke, S., Bartelt, C. und Stuckenschmidt, H. (2023). Outlying aspect mining via sum-product networks. In , Advances in knowledge discovery and data mining: 27th Pacific-Asia Conference on knowledge discovery and data mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023 : proceedings. Part I (S. 27–38). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Marton, S., Lüdtke, S., Bartelt, C. und Stuckenschmidt, H. (2023). GradTree: Learning axis-aligned decision trees with gradient descent. In , (S. 1–17). , Neural Information Processing Systems Foundation, Inc. (NeurIPS): New Orleans.
Moch, A. (2023). Provable security against generic attacks on stream ciphers. Journal of Mathematical Cryptology, 17, 1–27.
Moch, A. (2023). Provable security for lightweight message authentication and encryption. Dissertation. Mannheim.
Ott, S., Betz, P., Stepanova, D., Gad-Elrab, M. H., Meilicke, C. und Stuckenschmidt, H. (2023). Rule-based knowledge graph completion with canonical models. In , CIKM'23: Proceedings of the 32nd ACM International Conference on Information & Knowledge Management (S. 1971-1981). , ACM: Birmingham, United Kingdom.
Peeters, R. und Bizer, C. (2023). Using ChatGPT for Entity Matching. In , New Trends in Database and Information Systems : ADBIS 2023 short papers, doctoral consortium and workshops: AIDMA, DOING, K-Gals, MADEISD, PeRS, Barcelona, Spain, September 4–7, 2023, Proceedings (S. 221–230). Communications in Computer and Information Science, Springer: Cham.
Peeters, R., Der, R. C. und Bizer, C. (2023). WDC products: A multi-dimensional entity matching benchmark. In , Proceedings 27th International Conference on Extending Database Technology (EDBT 2024), Paestum, Italy, March 25 – March 28 (S. 22–33). OpenProceedings, OpenProceedings.org: Konstanz.
Preisner, P. und Paulheim, H. (2023). Universal preprocessing operators for embedding knowledge graphs with literals. In , DL4KG 2023 : Proceedings of the Workshop on Deep Learning for Knowledge Graphs (DL4KG 2023) co-located with the 21th International Semantic Web Conference (ISWC 2023), Athens, November 6–10, 2023 (S. 1–10). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Reinig, I. und Markert, K. (2023). Can current NLI systems handle German word order? Investigating language model performance on a new German challenge set of minimal pairs. In , The 15th International Conference on Computational Semantics : proceedings of the conference, June 21 – 23, 2023 Nancy, France (S. 1–15). , Association for Computational Linguistics: Nancy, France.
Renz-Wieland, A., Kieslinger, A., Gericke, R., Gemulla, R., Kaoudi, Z. und Markl, V. (2023). Good intentions: adaptive parameter management via intent signaling. In , CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (S. 2156-2166). , Association for Computing Machinery: New York, NY.
Rutesic, P., Pfisterer, D., Fischer, S. und Paulheim, H. (2023). Ontology-based models of chatbots for populating knowledge graphs. In , Knowledge Graphs and Semantic Web: 5th Iberoamerican Conference and 4th Indo-American Conference, KGSWC 2023, Zaragoza, Spain, November 13–15, 2023 : proceedings (S. 228–242). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Schlather, M., Freudenberg, A., Moerkotte, G., Pook, T. und Vandenplas, J. (2023). Software project „miraculix“: Efficient computations with large genomic datasets. In , Proceedings of the 2023 Interbull Meeting, Lyon, France, 26–27 August 2023 (S. 15–22). Interbull Bulletin, Swedish University of Agricultural Sciences (SLU): Uppsala.
Schlechtinger, M., Kosack, D., Paulheim, H., Fetzer, T. und Krause, F. (2023). The price of algorithmic pricing: Investigating collusion in a market simulation with AI agents. In , AAMAS '23: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (S. 2748-2750). , International Foundation for Autonomous Agents and Multiagent Systems: Richland, SC.
Schreckenberger, C., He, Y., Lüdtke, S., Bartelt, C. und Stuckenschmidt, H. (2023). Online random feature forests for learning in varying feature spaces. In , Proceedings of the 37th AAAI Conference on Artificial Intelligence. Vol. 4 (S. 4587-4595). , AAAI Press: Washington, DC.
Schäfer, B. (2023). Recognizing hand-drawn diagrams in images. Dissertation. Mannheim.
Schäfer, B., der Aa, H., Leopold, H. und Stuckenschmidt, H. (2023). Sketch2Process: End-to-end BPMN Sketch Recognition Based on Neural Networks. IEEE Transactions on Software Engineering, 49, 2621-2641.
Sola, D., der Aa, H., Meilicke, C. und Stuckenschmidt, H. (2023). Activity recommendation for business process modeling with pre-trained language models. In , The Semantic Web : 20th International Conference, ESWC 2023, Hersonissos, Crete, Greeece, May 28-June 1, 2023. Proceddings (S. 316–334). , Springer International Publishing: Cham, Switzerland.
Sola, D., Warmuth, C., Schäfer, B., Badakhshan, P., Rehse, J.-R. und Kampik, T. (2023). SAP Signavio Academic Models: A large process model dataset. In , Process Mining Workshops : ICPM 2022 International Workshops, Bozen-Bolzano, Italy, October 23–28, 2022, Revised Selected Papers (S. 453–465). Lecture Notes in Business Information Processing : LNBIP, Springer: Berlin [u. a.].
Sola, D. (2023). Recommending activities for business process models. Dissertation. Mannheim.
Sousa, R. T., Silva, S., Paulheim, H. und Pesquita, C. (2023). Biomedical knowledge graph embeddings with negative statements. In , The Semantic Web – ISWC 2023 : 22nd International Semantic Web Conference, Athens, Greece, November 6–10, 2023 : proceedings. Part I (S. 428–446). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Spreitzenbarth, J., Bode, C. und Stuckenschmidt, H. (2023). Designing an AI purchasing requisition bundling generator. Computers in Industry, 155, Article 104043, 1–14.
Spreitzenbarth, J., Bode, C. und Stuckenschmidt, H. (2023). Designing an AI-enabled bundling generator in an automotive case study. In , Proceedings of the 56th Annual Hawaii International Conference on System Sciences (S. 4495-4504). , University of Hawaii at Manoa: Honolulu, HI.
Steinmann, L., Nowotka, D., Oberländer, L., Pfuhl, H., Stuckenschmidt, H. und Drechsler, R. (2023). Workshop: Aktuelle Entwicklungen und Perspektiven (an Hochschulen) im Bereich Data Science. In , Informatik 2023 : designing futures: Zukünfte gestalten ; 26. – 29. September 2023, Berlin (S. 73–80). GI-Edition : Lecture Notes in Informatics. Proceedings, Ges. für Informatik: Bonn.
Theil, K., Hovy, D. und Stuckenschmidt, H. (2023). Top-down influence? Predicting CEO personality and risk impact from speech transcripts. In , Proceedings of the seventeenth International AAAI Conference on web and social media : June 5th – 8th 2023, Limassol, Cyprus (S. 832–841). International AAAI Conference on Web and Social Media, AAAI Press: Palo Alto, Calif..
Waltersdorfer, L., Breit, A., Ekaputra, F. J., Sabou, M., Ekelhart, A., Iana, A., Paulheim, H., Portisch, J., Revenko, A., Teije, A. . und van Harmelen, F. (2023). Semantic web machine learning systems: An analysis of system patterns. In Compendium of neurosymbolic artificial intelligence (S. 77–99). Amsterdam: IOS Press.
Wilken, N., Cohausz, L., Bartelt, C. und Stuckenschmidt, H. (2023). Planning landmark based goal recognition revisited: Does using initial state landmarks make sense? In , KI 2023: Advances in Artificial Intelligence : 46th Conference on AI, Berlin, Germany, September 26–29, 20023, proceedings (S. 231–244). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Yu, H.-C., Rehbein, I. und Ponzetto, S. P. (2023). Policy domain prediction from party manifestos with adapters and knowledge enhanced transformers. In , The 19th Conference on Natural Language Processing (KONVENS 2023) : proceedings of the conference, September 18–22, 2023 (S. 229–244). , Association for Computational Lingustics, ACL: Stroudsburg, PA.

2022

Alturki, S. (2022). Predicting students' academic achievement using methods of educational data mining. Dissertation. Mannheim.
Alturki, S., Cohausz, L. und Stuckenschmidt, H. (2022). Predicting master’s students’ academic performance: An empirical study in Germany. Smart Learning Environments, 9, 1–22.
Alturki, S., Hulpus, I. und Stuckenschmidt, H. (2022). Predicting academic outcomes: A survey from 2007 till 2018. Technology, Knowledge and Learning, 27, 275–307.
Alturki, S. und Stuckenschmidt, H. (2022). Assessing students' self-assessment ability in an interdisciplinary domain. Journal of Applied Research in Higher Education : JARHE, 14, 1449-1466.
Atkinson, C. und Kühne, T. (2022). Taming the complexity of digital twins. IEEE Software, 39, 27–32.
Bellan, P., der Aa, H., Dragoni, M., Ghidini, C. und Ponzetto, S. P. (2022). PET: An annotated dataset for process extraction from natural language text tasks. In , Business Process Management Workshops : BPM 2022 International Workshops, Münster, Germany, September 11–16, 2022, revised selected papers (S. 315–321). Lecture Notes in Business Information Processing : LNBIP, Springer: Berlin [u. a.].
Bellan, P., Ghidini, C., Dragoni, M., Ponzetto, S. P. und der Aa, H. (2022). Process extraction from natural language text: the PET dataset and annotation guidelines. In , NL4AI 2022 : Proceedings of the Sixth Workshop on Natural Language for Artificial Intelligence (NL4AI 2022), co-located with 21th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2022), Udine, November 30th, 2022 (S. 165–179). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Betz, P., Meilicke, C. und Stuckenschmidt, H. (2022). Adversarial explanations for knowledge graph embeddings. In , Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence : Vienna, 23–29 July 2022 (S. 2820-2826). , International Joint Conferences on Artificial Intelligence: Darmstadt ; Vienna.
Betz, P., Meilicke, C. und Stuckenschmidt, H. (2022). Supervised knowledge aggregation for knowledge graph completion. In , The semantic web: 19th International Conference, ESWC 2022, Hersonissos, Crete, Greece, May 29-June 2, 2022 : proceedings (S. 74–92). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Bombieri, M., Rospocher, M., Ponzetto, S. P. und Fiorini, P. (2022). The robotic surgery procedural framebank. In , Language Resources and Evaluation Conference, LREC 2022, 20–25 June 2022, Palais du Pharo, Marseille, France : conference proceedings (S. 3950-3959). , European Language Resources Association (ELRA): Paris.
Brendle, M., Weber, N., Vallyev, M., May, N., Schulze, R., Böhm, A., Moerkotte, G. und Grossniklaus, M. (2022). SAHARA: Memory footprint reduction of cloud databases with automated table partitioning. In , Proceedings of the 25th International Conference on Extending Database Technology, EDBT 2022. Edinburgh, UK, March 29 – April 1 (S. 13–26). Advances in Database Technology, OpenProceedings.org: Konstanz.
Cohausz, L. (2022). Towards real interpretability of student success prediction combining methods of XAI and social science. In , Proceedings of the 15th International Conference on Educational Data Mining (S. 361–367). , International Educational Data Mining Society: Durham.
Cohausz, L. (2022). When probabilities are not enough – A framework for causal explanations of student success models. Journal of Educational Data Mining, 14, 52–75.
Cohausz, L., Wilken, N. und Stuckenschmidt, H. (2022). Plan-similarity based heuristics for goal recognition. In , 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) : PerCom Workshops 2022 (S. 316–321). , IEEE: Pisa.
Flachs, D., Müller, M. und Moerkotte, G. (2022). The 3D hash join: Building on non-unique join attributes. In , 12th Conference on Innovative Data Systems Research, CIDR 2022, Chaminade, Ca, USA, January 9–12, 2022 (S. 1–9). , CIDR: Chaminade.
Friede, D. und Niepert, M. (2022). Efficient learning of discrete-continuous computation graphs. In , 35th Conference on Neural Information Processing Systems (NeurIPS 2021) : online, 6–14 December 2021 (S. 6720-6732). Advances in Neural Information Processing Systems, Curran Associates: Red Hook, NY.
Hamann, M., Moch, A., Krause, M. und Mikhalev, V. (2022). The DRACO stream cipher: a power-efficient small-state stream cipher with full provable security against TMDTO attacks. IACR Transactions on Symmetric Cryptology, 2022, 1–42.
Heist, N. und Paulheim, H. (2022). Transformer-based subject entity detection in Wikipedia listings. In , Proceedings of the 5th Workshop on Deep Learning for Knowlege Graphs (DL4KG 2022) co-located with the 21th International Semantic Web Conference (ISWC 2022) (S. 1–16). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Holtermann, C., Lauscher, A. und Ponzetto, S. P. (2022). Fair and argumentative language modeling for computational argumentation. In , The 60th Annual Meeting of the Association for Computational Linguistics : proceedings of the conference, May 22–27, 2022 (S. 7841-7861). , Association for Computational Linguistics (ACL): Stroudsburg, PA.
Hung, C.-C., Green, T., Litschko, R., Tsereteli, T., Takeshita, S., Bombieri, M., Glavaš, G. und Ponzetto, S. P. (2022). ZusammenQA: Data augmentation with specialized models for cross-lingual open-retrieval question answering system. In , Proceedings of the Workshop on Multilingual Information Access (MIA) (S. 77–90). , Association for Computational Linguistics: Seattle, USA.
Hung, C.-C., Lauscher, A., Ponzetto, S. P. und Glavaš, G. (2022). DS-TOD: Efficient domain specialization for task-oriented dialog. In , The 60th Annual Meeting of the Association for Computational Linguistics, Findings of ACL 2022 : May 22–27, 2022 (S. 891–904). , Association for Computational Linguistics (ACL): Stroudsburg, PA.
Hung, C.-C., Lauscher, A., Vulić, I., Ponzetto, S. P. und Glavaš, G. (2022). Multi2WOZ: A robust multilingual dataset and conversational pretraining for task-oriented dialog. In , The 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies : proceedings of the conference, July 10–15, 2022 (S. 3687-3703). , Association for Computational Linguistics (ACL): Stroudsburg, PA.
Kappenberger, J., Theil, K. und Stuckenschmidt, H. (2022). Evaluating the impact of AI-based priced parking with social simulation. In , Social Informatics: 13th International Conference, SocInfo 2022, Glasgow, UK, October 19–21, 2022, proceedings (S. 54–75). Lecture Notes in Computer Science, Springer: Berlin [u. a.].
Kessel, M. und Atkinson, C. (2022). Diversity-driven unit test generation. The Journal of Systems and Software : JSS, 193, 1–22.
Knorr, L. und Portisch, J. (2022). Fine-TOM matcher results for OAEI 2021. In , OM 2021, Ontology Matching 2021 : Proceedings of the 16th International Workshop on Ontology Matching, co-located with the 20th International Semantic Web Conference (ISWC 2021), virtual conference, October 25, 2021 (S. 144–151). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Korini, K., Peeters, R. und Bizer, C. (2022). SOTAB: The WDC Schema.org table annotation benchmark. In , SemTab 2022 : Proceedings of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching, co-located with the 21st International semantic Web Conference (ISWC 2022), virtual conference, October 23–27, 2022 (S. 14–19). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Kossack, D., Borg, N., Knorr, L. und Portisch, J. (2022). TOM matcher results for OAEI 2021. In , OM 2021, Ontology Matching 2021 : Proceedings of the 16th International Workshop on Ontology Matching, co-located with the 20th International Semantic Web Conference (ISWC 2021), virtual conference, October 25, 2021 (S. 193–198). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Kühne, T. und Lange, A. (2022). Melanee and DLM: a contribution to the MULTI collaborative comparison challenge. In , MODELS '22 : proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings (S. 434–443). , ACM: New York, NY.
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Litschko, R., Vulić, I., Ponzetto, S. P. und Glavaš, G. (2022). On cross-lingual retrieval with multilingual text encoders. Information Retrieval Journal, 25, 149–183.
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Publikationen des Instituts für Informatik und Wirtschaftsinformatik

2025

2024

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2022

Dekanat der Fakultät für Wirtschaftsinformatik und Wirtschaftsmathematik

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