Publications

2024

Betz, P., Galarraga, L., Ott, S., Meilicke, C., Suchanek, F. M. and 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. and 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.].
Brinkmann, A., Baumann, N. and 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. and 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.].
Cohausz, L., Kappenberger, J. and 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.
Gastinger, J., Meilicke, C., Errica, F., Sztyler, T., Schuelke, A. and 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. and 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.].
Iana, A., Alam, M. and Paulheim, H. (2024). A survey on knowledge-aware news recommender systems. Semantic Web, 15, 21–82.
Iana, A., Glavaš, G. and 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.
Kadel, P., Heist, N., Paulheim, H. and 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. and 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: .
Marton, S., Lüdtke, S., Bartelt, C. and 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. and 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. and 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. and Stuckenschmidt, H. (2024). Anytime bottom-up rule learning for large-scale knowledge graph completion. The VLDB Journal, 33, 131–161.
Peeters, R., Brinkmann, A. and 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. and 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. and 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. and 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., Rehbein, I. and 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.
Schlechtinger, M., Kosack, D., Krause, F. and 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. and 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. and 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. and Ponzetto, S. P. (2024). Cross-lingual extreme summarization of scholarly documents. International Journal on Digital Libraries, 25, 249–271.
Tschalzev, A., Nitschke, P., Kirchdorfer, L., Lüdtke, S., Bartelt, C. and 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.
Wilken, N., Cohausz, L., Bartelt, C. and Stuckenschmidt, H. (2024). Fact Probability Vector Based Goal Recognition. In , tba (S. tba-tba). , tba: tba.

2023

Baumgartner, M., Dell'Aglio, D., Paulheim, H. and 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. and Paulheim, H. (2023). Knowledge graph embeddings: open challenges and opportunities. Transactions on Graph Data and Knowledge : TGDK, 1, 1–32.
Bizer, C., Heath, T. and 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. and 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. . and 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. and 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. and 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. and Detzler, S. (2023). Wildfire prediction for California using and comparing Spatio-Temporal Knowledge Graphs. Information Technology : IT, 65, 189–199.
Böckling, M., Paulheim, H. and 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. and 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. and 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. and 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.].
Friede, D. (2023). Exploring discrete representations in stochastic computation graphs: Challenges, benefits, and novel strategies. Dissertation. Mannheim.
Friede, D., Reimers, C., Stuckenschmidt, H. and 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. and 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.].
Green, T., Ponzetto, S. P. and 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. and 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. and 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. and 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. and 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. and 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. and 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. and 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. and 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. and 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. and 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. and 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. and 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.
Klamm, C., Rehbein, I. and 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. and 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. and 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. and 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. and 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. and 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. and 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. and Ponzetto, S. P. (2023). Data-driven prototyping via natural-language-based GUI retrieval. Automated Software Engineering, 30, 1–34.
Korini, K. and 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. and 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.].
Li, Y., Martschat, S. and 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. and 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.
Lukasik, J. (2023). Topology Learning for Prediction, Generation, and Robustness in Neural Architecture Search. Dissertation. Mannheim.
Lüdtke, S., Bartelt, C. and 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. and 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.
Ott, S., Betz, P., Stepanova, D., Gad-Elrab, M. H., Meilicke, C. and 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. and 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. and 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. and 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. and 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. and 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. and 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.].
Schlechtinger, M., Kosack, D., Paulheim, H., Fetzer, T. and 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. and 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. and 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. and 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. and 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. and 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. and Stuckenschmidt, H. (2023). Designing an AI purchasing requisition bundling generator. Computers in Industry, 155, Article 104043, 1–14.
Spreitzenbarth, J., Bode, C. and 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.
Theil, K., Hovy, D. and 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. . and 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. and 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.].

2022

Alturki, S. (2022). Predicting students' academic achievement using methods of educational data mining. Dissertation. Mannheim.
Alturki, S., Cohausz, L. and Stuckenschmidt, H. (2022). Predicting master’s students’ academic performance: An empirical study in Germany. Smart Learning Environments, 9, 1–22.
Alturki, S., Hulpus, I. and Stuckenschmidt, H. (2022). Predicting academic outcomes: A survey from 2007 till 2018. Technology, Knowledge and Learning, 27, 275–307.
Alturki, S. and Stuckenschmidt, H. (2022). Assessing students' self-assessment ability in an interdisciplinary domain. Journal of Applied Research in Higher Education : JARHE, 14, 1449-1466.
Bellan, P., der Aa, H., Dragoni, M., Ghidini, C. and 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. and 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. and 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. and 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. and 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.
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. and 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.
Friede, D. and 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.
Heist, N. and 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. and 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. and 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. and 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. and 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. and 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.].
Knorr, L. and 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. and 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. and 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.
Litschko, R., Vulić, I., Ponzetto, S. P. and Glavaš, G. (2022). On cross-lingual retrieval with multilingual text encoders. Information Retrieval Journal, 25, 149–183.
Lüdtke, S., Bartelt, C. and Stuckenschmidt, H. (2022). Exchangeability-aware sum-product networks. In , Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, Vienna, 23–29 July 2022 (S. 4864-4870). , International Joint Conferences on Artificial Intelligence Organization: Wien.
Marton, S., Lüdtke, S. and Bartelt, C. (2022). Explanations for neural networks by neural networks. Applied Sciences, 12, 1–14.
Peeters, R. and Bizer, C. (2022). Cross-language learning for product matching. In , Companion Proceedings of the Web Conference 2022 (S. 236–238). , ACM: New York, NY.
Peeters, R. and Bizer, C. (2022). Integrating product data using deep learning : Art.-Nr. 11. In , Proceedings of the 7th bwHPC Symposium (S. 59–62). , Universität Ulm: Ulm.
Peeters, R. and Bizer, C. (2022). Supervised contrastive learning for product matching. In , Companion Proceedings of the Web Conference 2022 (S. 248–251). , ACM: New York, NY.
Portisch, J. (2022). Exploiting general-purpose background knowledge for automated schema matching. Dissertation. Mannheim.
Portisch, J., Heist, N. and Paulheim, H. (2022). Knowledge graph embedding for data mining vs. knowledge graph embedding for link prediction – two sides of the same coin? Semantic Web, 13, 399–422.
Portisch, J., Hladik, M. and Paulheim, H. (2022). Background knowledge in ontology matching : a survey. Semantic Web, 55, 1–55.
Portisch, J. and Paulheim, H. (2022). ALOD2vec 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. 117–123). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Portisch, J. and Paulheim, H. (2022). The DLCC node classification benchmark for analyzing knowledge graph embeddings. In , The Semantic Web – ISWC 2022 : 21st International Semantic Web Conference, virtualeEvent, October 23–27, 2022, proceedings (S. 592–609). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
Portisch, J. and Paulheim, H. (2022). Wiktionary 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. 199–206). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Primpeli, A. (2022). Reducing the labeling effort for entity resolution using distant supervision and active learning. Dissertation. Mannheim.
Primpeli, A. and Bizer, C. (2022). Impact of the characteristics of multi-source entity matching tasks on the performance of active learning methods. In , The Semantic Web : 19th International Conference, ESWC 2022, Hersonissos, Crete, Greece, May 29 – June 2, 2022, proceedings (S. 113–129). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
Rajula, P., Hung, C.-C. and Ponzetto, S. P. (2022). Stacked model based argument extraction and stance detection using embedded LSTM model. In , CLEF 2022 : Proceedings of the Working Notes of CLEF 2022 – Conference and Labs of the Evaluation Forum, Bologna, Italy, September 5th to 8th, 2022 (S. 3064-3073). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Rana, A., Golchha, P., Juntunen, R., Coajă, A., Elzamarany, A., Hung, C.-C. and Ponzetto, S. P. (2022). LeviRANK: Limited query expansion with voting integration for document retrieval and ranking : notebook for the touché lab on argument retrieval at CLEF 2022. In , CLEF 2022 : Proceedings of the Working Notes of CLEF 2022 – Conference and Labs of the Evaluation Forum, Bologna, Italy, September 5th to 8th, 2022 (S. 3074-3089). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Renz-Wieland, A., Gemulla, R., Kaoudi, Z. and Markl, V. (2022). NuPS: A parameter server for machine learning with non-uniform parameter access. In , SIGMOD '22 : proceedings of the 2022 International Conference on Management of Data : June 12–17, 2022, Philadelphia, PA, USA (S. 481–495). , ACM: New York, NY.
Saxena, A., Kochsiek, A. and Gemulla, R. (2022). Sequence-to-sequence knowledge graph completion and question answering. In , Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics. Volume 1 Long Papers (S. 2814-2828). , Association for Computational Linguistics: Stroudsburg, PA.
Schreckenberger, C., Bartelt, C. and Stuckenschmidt, H. (2022). Dynamic forest for learning from data streams with varying feature spaces. In , Cooperative information systems : 28th International Conference, CoopIS 2022, Bozen-Bolzano, Italy, October 4–7, 2022, Proceedings (S. 95–111). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
Sola, D., der Aa, H., Meilicke, C. and Stuckenschmidt, H. (2022). Exploiting Label Semantics For Rule-Based Activity Recommendation In Business Process Modeling. Information Systems : IS, 108.
Sola, D., Meilicke, C., der Aa, H. and Stuckenschmidt, H. (2022). On the Use of Knowledge Graph Completion Methods for Activity Recommendation in Business Process Modeling. In , Business Process Management Workshops : BPM 2021 international workshops, Rome, Italy, September 6–10, 2021, revised selected papers (S. 5–17). Lecture Notes in Business Information Processing : LNBIP, Springer: Berlin [u.a.].
Takeshita, S., Green, T., Friedrich, N., Eckert, K. and Ponzetto, S. P. (2022). X-SCITLDR: Cross-lingual extreme summarization of scholarly documents. In , JCDL '22 : Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2022 : hybrid conference, Colone, Germany and online, June 20 -24, 2022 (S. 1–12). , ACM: München.
Theil, C. (2022). Uncertainty, risk, and financial disclosures : applications of natural language processing in behavioral economics. Dissertation. Mannheim.
Tsereteli, T., Kartal, Y. S., Ponzetto, S. P., Zielinski, A., Eckert, K. and Mayr, P. (2022). Overview of the SV-ident 2022 shared task on survey variable identification in social science publications. In , Proceedings of the Third Workshop on Scholarly Document Processing (S. 229–246). COLING / International Committee on Computational Linguistics, Association for Computational Linguistics: New York, NY.
Wilken, N., Cohausz, L., Schaum, J., Lüdtke, S., Bartelt, C. and Stuckenschmidt, H. (2022). Leveraging planning landmarks for hybrid online goal recognition. In , International Conference on Automated Planning and Scheduling ICAPS (2022) : June 13–17, 2022, virtual (S. ). , CEUR Workshop Proceedings: Aachen.

2021

Verborgh, R., Hose, K., Paulheim, H., Champin, P.-A., Maleshkova, M., Corcho, O., Ristoski, P. and Alam, M. (eds.) (2021). The semantic web – 18th international conference, ESWC 2021, virtual event, June 6–10, 2021, proceedings. Berlin [u.a.]: Springer.
Abd Nikooie Pour, M., Algergawy, A., Amardeilh, F., Amini, R., Fallatah, O., Faria, D., Fundulaki, I., Harrow, I., Hertling, S., Hitzler, P., Huschka, M., Ibanescu, L., Jiménez-Ruiz, E., Karam, N., Laadhar, A., Lambrix, P., Li, H., Li, Y., Michel, F., Nasr, E., Paulheim, H., Pesquita, C., Portisch, J., Roussey, C., Saveta, T., Shvaiko, P., Splendiani, A., Trojahn, C., Vataščinová, J., Yaman, B., Zamazal, O. and Zhou, L. (2021). Results of the Ontology Alignment Evaluation Initiative 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. 62–108). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Alhersh, T. (2021). From motion to human activity recognition. Dissertation. Mannheim.
Alhersh, T., Stuckenschmidt, H., Rehman, A. U. and Brahim Belhaouari, S. (2021). Learning human activity from visual data using deep learning. IEEE Access, 9, 106245-106253.
Alturki, S. and Alturki, N. (2021). Using educational data mining to predict students' academic performance for applying early interventions. Journal of Information Technology Education : JITE. Innovations in Practice : IIP, 20, 121–137.
Biswas, R., Sofronova, R., Alam, M., Heist, N., Paulheim, H. and Sack, H. (2021). Do judge an entity by its name! Entity typing using language models. In , The Semantic Web: ESWC 2021 Satellite Events : virtual event, June 6–10, 2021, revised selected papers (S. 65–70). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
Brinkmann, A. and Bizer, C. (2021). Improving hierarchical product classification using domain-specific language modelling. Bulletin of the Technical Committee on Data Engineering / IEEE Computer Society, 44, 14–25.
Brockmeier, M., Liu, Y., Pateer, S., Hertling, S. and Paulheim, H. (2021). On-demand and lightweight knowledge graph generation – a demonstration with DBpedia. In , Joint proceedings of the Semantics co-located events: Poster&Demo track and Workshop on Ontology-Driven Conceptual Modelling of Digital Twins co-located with Semantics 2021, Amsterdam and Online, September 6–9, 2021 (S. 1–5). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Bucher, T.-C., Jiang, X., Meyer, O., Waitz, S., Hertling, S. and Paulheim, H. (2021). Scikit-learn pipelines meet knowledge graphs. In , The semantic web: ESWC 2021 Satellite Events : virtual event, June 6–10, 2021, revisted selected papers (S. 9–14). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
Burzlaff, F. (2021). Knowledge-driven architecture composition. Dissertation. Mannheim.
Bühler, B. and Paulheim, H. (2021). Web table classification based on visual features. In , Web Engineering : 21st International Conference, ICWE 2021, Biarritz, France, May 18–21, 2021, Proceedings (S. 185–200). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
Civitarese, G., Sztyler, T., Riboni, D., Bettini, C. and Stuckenschmidt, H. (2021). POLARIS: Probabilistic and ontological activity recognition in smart-homes. IEEE Transactions on Knowledge and Data Engineering : TKDE, 33, 209–223.
Diete, A. (2021). Towards multimodal activity recognition in complex scenarios. Dissertation. Mannheim.
Frendo, O. (2021). Improving smart charging for electric vehicle fleets by integrating battery and prediction models. Dissertation. Mannheim.
Frendo, O., Gaertner, N. and Stuckenschmidt, H. (2021). Open source algorithm for smart charging of electric vehicle fleets. IEEE Transactions on Industrial Informatics, 17, 6014-6022.
Frendo, O., Gärtner, N. and Stuckenschmidt, H. (2021). Improving smart charging prioritization by predicting electric vehicle departure time. IEEE Transactions on Intelligent Transportation Systems, 22, 6646-6653.
Friedrich, N., Lauscher, A., Ponzetto, S. P. and Glavaš, G. (2021). DebIE: A platform for implicit and explicit debiasing of word embedding spaces. In , The 16th Conference of the European Chapter of the Association for Computational Linguistics : proceedings of the System Demonstrations, April 19–23, 2021 (S. 91–98). , Association for Computational Linguistics (ACL): Stroudsburg, PA.
Ghanem, B., Ponzetto, S. P., Rosso, P. and Rangel, F. (2021). FakeFlow: Fake news detection by modeling the flow of affective information. In , The 16th Conference of the European Chapter of the Association for Computational Linguistics : proceedings of the conference, April 19–23, 2021 (S. 679–689). , Association for Computational Linguistics (ACL): Stroudsburg, PA.
Heist, N., Hertling, S., Ringler, D. and Paulheim, H. (2021). Wissensgraphen im Web : Überblick und Vergleich. In Semantische Datenintelligenz im Einsatz (S. 127–151). Wiesbaden: Springer Vieweg.
Heist, N. and Paulheim, H. (2021). Information extraction from co-occurring similar entities. In , The Web Conference 2021 : Proceedings of the World Wide Web Conference WWW 2021 (S. 3999-4009). , Association for Computing Machinery: New York, NY [u.a.].
Heist, N. and Paulheim, H. (2021). The CaLiGraph ontology as a challenge for OWL reasoners. In , Semantic Reasoning Evaluation Challenge 2021 : proceedings of the Semantic Reasoning Evaluation Challenge (SemREC 2021), co-located with the 20th International Semantic Web Conference (ISWC 2021); virtual event, October 27th, 2021 (S. 21–31). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Helmstetter, S. and Paulheim, H. (2021). Collecting a large scale dataset for classifying fake news tweets using weak supervision. Future Internet, 13, 114.
Hertling, S. and Paulheim, H. (2021). ATBox 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. 137–143). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Hertling, S. and Paulheim, H. (2021). Order matters: Matching multiple knowledge graphs. In , K-CAP '21: Proceedings of the 11th on Knowledge Capture Conference (S. 113–120). , Association for Computing Machinery: New York, NY.
Hertling, S., Portisch, J. and Paulheim, H. (2021). Matching with transformers in MELT. 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. 13–24). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Hoffmann, L., Bartelt, C. and Stuckenschmidt, H. (2021). Knowledge injection via ML-based initialization of neural networks. In , Proceedings of the CIKM 2021 Workshops (CIKMW 2021) co-located with 30th ACM International Conference on Information and Knowledge Management (CIKM 2021) : Gold Coast, Queensland, Australia, November 1–5,2021 (S. 1–6). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Huber, J. and Stuckenschmidt, H. (2021). Intraday shelf replenishment decision support for perishable goods. International Journal of Production Economics, 231, 1–14.
Iana, A. and Paulheim, H. (2021). GraphConfRec: A Graph Neural Network-Based Conference Recommender System. In , 2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL), Sept. 27 2021 to Sept. 30 2021, Champaign, IL, USA : conference proceedings (S. 90–99). , IEEE: New York, NY.
Kochsiek, A. and Gemulla, R. (2021). Parallel training of knowledge graph embedding models: a comparison of techniques. In , (S. 633–645). Proceedings of the VLDB Endowment, Association of Computing Machinery: New York, NY.
Lauscher, A. (2021). Language representations for computational argumentation. Dissertation. Mannheim.
Litschko, R., Vulić, I., Ponzetto, S. P. and Glavaš, G. (2021). Evaluating multilingual text encoders for unsupervised cross-lingual retrieval. In , Advances in information retrieval : 43rd European Conference on IR Research, ECIR 2021, virtual event, March 28 – April 1, 2021, proceedings, part I (S. 342–358). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
Meilicke, C., Betz, P. and Stuckenschmidt, H. (2021). Why a naive way to combine symbolic and latent knowledge base completion works surprisingly well. In , 3rd Conference on Automated Knowledge Base Construction (S. 1–26). , OpenReview.net: Online.
Metzger, N., Hoffmann, L., Bartelt, C., Stuckenschmidt, H., Wommer, M. and Bescos del Castillo, M. B. (2021). Towards trace-graphs for data-driven test case mining in the domain of automated driving. In , Third IEEE International Conference on Artificial Intelligence Testing: AITest 2021 : proceedings : 23–26 August 2021, online event (S. 41–48). , IEEE: Piscataway, NJ.
Nolle, A. (2021). Federated knowledge base debugging in DL-Lite A. Dissertation. Mannheim.
Nolte, F., Wilken, N. and Bartelt, C. (2021). Rendezvous delivery: Utilizing autonomous electric vehicles to improve the efficiency of last mile parcel delivery in urban areas. In , 2021 IEEE PerCom Workshops : PerAwareCity 2021, 6th IEEE Workshop on Pervasive Context-Aware Smart Cities and Intelligent Transportation Systems, March 22–26, 2021 in Kassel, Germany (S. 148–153). , IEEE Computer Society: Piscataway, NJ.
Peeters, R. and Bizer, C. (2021). Dual-objective fine-tuning of BERT for entity matching. In , 47th International Conference on Very Large Data Bases (VLDB 2021) : Copenhagen, Denmark, August 16–20, 2021 (S. 1913-1921). Proceedings of the VLDB Endowment, Association of Computing Machinery: New York, NY.
Pernpeintner, M., Bartelt, C. and Stuckenschmidt, H. (2021). Governing black-box agents in competitive multi-agent systems. In , Multi-Agent Systems : 18th European Conference, EUMAS 2021, virtual event, June 28–29, 2021, revised selected papers (S. 19–36). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
Portisch, J., Hladik, M. and Paulheim, H. (2021). Background knowledge in schema matching: Strategy vs. data. In , The Semantic Web – ISWC 2021 : 20th International Semantic Web Conference, ISWC 2021, virtual event, October 24–28, 2021, proceedings (S. 287–303). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
Portisch, J., Hladik, M. and Paulheim, H. (2021). FinMatcher at FinSim-2: hypernym detection in the financial services domain using knowledge graphs. In , Companion Proceedings of the Web Conference 2021 (S. 293–297). , Association for Computing Machinery: New York, NY, USA.
Portisch, J. and Paulheim, H. (2021). Putting RDF2vec in order. In , International Semantic Web Conference (ISWC) 2021: posters, demos and industry tracks: proceedings (S. 1–5). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
Primpeli, A. and Bizer, C. (2021). Graph-boosted active learning for multi-source entity resolution. In , The Semantic Web – ISWC 2021 : 20th international semantic web conference, ISWC 2021, virtual event, October 24–28, 2021, proceedings (S. 182–199). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
Renz-Wieland, A., Drobisch, T., Kaoudi, Z., Gemulla, R. and Markl, V. (2021). Just move it! Dynamic parameter allocation in action. In , 47th International Conference on Very Large Data Bases (VLDB 2021) : Copenhagen, Denmark, August 16–20, 2021 (S. 2707-2710). Proceedings of the VLDB Endowment, Association of Computing Machinery: New York, NY.
Rovera, M., Nanni, F. and Ponzetto, S. P. (2021). Event-based access to historical Italian war memoirs. ACM Journal on Computing and Cultural Heritage : JOCCH, 14, 1–23.
Schlechtinger, M., Kosack, D., Paulheim, H. and Fetzer, T. (2021). How algorithms work and play together. Concurrences : Revue des Droits de la Concurrence, 2021, 19–23.
Schlechtinger, M., Kosack, D., Paulheim, H. and Fetzer, T. (2021). Winning at any cost – infringing the cartel prohibition with reinforcement learning. In , Advances in Practical Applications of Agents, Multi-Agent Systems, and Social Good : The PAAMS collection, 19th international conference, PAAMS 2021, Salamanca, Spain, October 6–8, 2021, proceedings (S. 255–266). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
Schäfer, B., der Aa, H., Leopold, H. and Stuckenschmidt, H. (2021). Sketch2BPMN: Automatic recognition of hand-drawn BPMN models. In , Advanced Information Systems Engineering : 33rd International Conference, CAiSE 2021, Melbourne, VIC, Australia, June 28 – July 2, 2021, proceedings (S. 344–360). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
Schäfer, B., Keuper, M. and Stuckenschmidt, H. (2021). Arrow R-CNN for handwritten diagram recognition. International Journal on Document Analysis and Recognition : IJDAR, 24, 3–17.
Schäfer, B. and Stuckenschmidt, H. (2021). DiagramNet: hand-drawn diagram recognition using visual arrow-relation detection. In , Document Analysis and Recognition – ICDAR 2021 : 16th International Conference, Lausanne, Switzerland, September 5–10, 2021, Proceedings, Part I (S. 614–630). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
Sola, D. (2021). Towards a rule-based recommendation approach for business process modeling. In , Service-oriented computing – ICSOC 2020 Workshops : AIOps, CFTIC, STRAPS, AI-PA, AI-IOTS, and Satellite Events, Dubai, United Arab Emirates, December 14–17, 2020 : proceedings (S. 25–31). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
Sola, D., Meilicke, C., der Aa, H. and Stuckenschmidt, H. (2021). A rule-based recommendation approach for business process modeling. In , Advanced information systems engineering : 33rd International Conference, CAiSE 2021, Melbourne, VIC, Australia, June 28 – July 2, 2021, proceedings (S. 328–343). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
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