--- _id: '43395' author: - first_name: Roman full_name: Trentinaglia, Roman id: '49934' last_name: Trentinaglia orcid: 0000-0001-9728-4991 - first_name: Sven full_name: Merschjohann, Sven id: '11394' last_name: Merschjohann - first_name: Markus full_name: Fockel, Markus id: '8472' last_name: Fockel orcid: 0000-0002-1269-0702 - first_name: Hendrik full_name: Eikerling, Hendrik id: '29279' last_name: Eikerling citation: ama: 'Trentinaglia R, Merschjohann S, Fockel M, Eikerling H. Eliciting Security Requirements – An Experience Report. In: REFSQ 2023: Requirements Engineering: Foundation for Software Quality. Springer Nature Switzerland; 2023. doi:10.1007/978-3-031-29786-1_25' apa: 'Trentinaglia, R., Merschjohann, S., Fockel, M., & Eikerling, H. (2023). Eliciting Security Requirements – An Experience Report. REFSQ 2023: Requirements Engineering: Foundation for Software Quality. https://doi.org/10.1007/978-3-031-29786-1_25' bibtex: '@inproceedings{Trentinaglia_Merschjohann_Fockel_Eikerling_2023, place={Cham}, title={Eliciting Security Requirements – An Experience Report}, DOI={10.1007/978-3-031-29786-1_25}, booktitle={REFSQ 2023: Requirements Engineering: Foundation for Software Quality}, publisher={Springer Nature Switzerland}, author={Trentinaglia, Roman and Merschjohann, Sven and Fockel, Markus and Eikerling, Hendrik}, year={2023} }' chicago: 'Trentinaglia, Roman, Sven Merschjohann, Markus Fockel, and Hendrik Eikerling. “Eliciting Security Requirements – An Experience Report.” In REFSQ 2023: Requirements Engineering: Foundation for Software Quality. Cham: Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-29786-1_25.' ieee: 'R. Trentinaglia, S. Merschjohann, M. Fockel, and H. Eikerling, “Eliciting Security Requirements – An Experience Report,” 2023, doi: 10.1007/978-3-031-29786-1_25.' mla: 'Trentinaglia, Roman, et al. “Eliciting Security Requirements – An Experience Report.” REFSQ 2023: Requirements Engineering: Foundation for Software Quality, Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-29786-1_25.' short: 'R. Trentinaglia, S. Merschjohann, M. Fockel, H. Eikerling, in: REFSQ 2023: Requirements Engineering: Foundation for Software Quality, Springer Nature Switzerland, Cham, 2023.' date_created: 2023-04-04T12:47:31Z date_updated: 2023-04-04T12:51:41Z department: - _id: '241' - _id: '662' doi: 10.1007/978-3-031-29786-1_25 language: - iso: eng place: Cham publication: 'REFSQ 2023: Requirements Engineering: Foundation for Software Quality' publication_identifier: isbn: - '9783031297854' - '9783031297861' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer Nature Switzerland status: public title: Eliciting Security Requirements – An Experience Report type: conference user_id: '8472' year: '2023' ... --- _id: '44769' author: - first_name: Jannik full_name: Castenow, Jannik id: '38705' last_name: Castenow - first_name: Jonas full_name: Harbig, Jonas id: '47213' last_name: Harbig - first_name: Friedhelm full_name: Meyer auf der Heide, Friedhelm id: '15523' last_name: Meyer auf der Heide citation: ama: 'Castenow J, Harbig J, Meyer auf der Heide F. Unifying Gathering Protocols for Swarms of Mobile Robots. In: Lecture Notes in Computer Science. Springer International Publishing; 2023. doi:10.1007/978-3-031-30448-4_1' apa: Castenow, J., Harbig, J., & Meyer auf der Heide, F. (2023). Unifying Gathering Protocols for Swarms of Mobile Robots. In Lecture Notes in Computer Science. Springer International Publishing. https://doi.org/10.1007/978-3-031-30448-4_1 bibtex: '@inbook{Castenow_Harbig_Meyer auf der Heide_2023, place={Cham}, title={Unifying Gathering Protocols for Swarms of Mobile Robots}, DOI={10.1007/978-3-031-30448-4_1}, booktitle={Lecture Notes in Computer Science}, publisher={Springer International Publishing}, author={Castenow, Jannik and Harbig, Jonas and Meyer auf der Heide, Friedhelm}, year={2023} }' chicago: 'Castenow, Jannik, Jonas Harbig, and Friedhelm Meyer auf der Heide. “Unifying Gathering Protocols for Swarms of Mobile Robots.” In Lecture Notes in Computer Science. Cham: Springer International Publishing, 2023. https://doi.org/10.1007/978-3-031-30448-4_1.' ieee: 'J. Castenow, J. Harbig, and F. Meyer auf der Heide, “Unifying Gathering Protocols for Swarms of Mobile Robots,” in Lecture Notes in Computer Science, Cham: Springer International Publishing, 2023.' mla: Castenow, Jannik, et al. “Unifying Gathering Protocols for Swarms of Mobile Robots.” Lecture Notes in Computer Science, Springer International Publishing, 2023, doi:10.1007/978-3-031-30448-4_1. short: 'J. Castenow, J. Harbig, F. Meyer auf der Heide, in: Lecture Notes in Computer Science, Springer International Publishing, Cham, 2023.' date_created: 2023-05-11T13:13:45Z date_updated: 2023-05-11T13:14:43Z department: - _id: '63' doi: 10.1007/978-3-031-30448-4_1 language: - iso: eng place: Cham project: - _id: '106' name: 'Algorithmen für Schwarmrobotik: Verteiltes Rechnen trifft Dynamische Systeme' publication: Lecture Notes in Computer Science publication_identifier: isbn: - '9783031304477' - '9783031304484' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer International Publishing status: public title: Unifying Gathering Protocols for Swarms of Mobile Robots type: book_chapter user_id: '38705' year: '2023' ... --- _id: '46516' abstract: - lang: eng text: Linked knowledge graphs build the backbone of many data-driven applications such as search engines, conversational agents and e-commerce solutions. Declarative link discovery frameworks use complex link specifications to express the conditions under which a link between two resources can be deemed to exist. However, understanding such complex link specifications is a challenging task for non-expert users of link discovery frameworks. In this paper, we address this drawback by devising NMV-LS, a language model-based verbalization approach for translating complex link specifications into natural language. NMV-LS relies on the results of rule-based link specification verbalization to apply continuous training on T5, a large language model based on the Transformerarchitecture. We evaluated NMV-LS on English and German datasets using well-known machine translation metrics such as BLUE, METEOR, ChrF++ and TER. Our results suggest that our approach achieves a verbalization performance close to that of humans and outperforms state of the art approaches. Our source code and datasets are publicly available at https://github.com/dice-group/NMV-LS. author: - first_name: Abdullah Fathi Ahmed full_name: Ahmed, Abdullah Fathi Ahmed id: '29670' last_name: Ahmed - first_name: Asep Fajar full_name: Firmansyah, Asep Fajar id: '76787' last_name: Firmansyah - first_name: Mohamed full_name: Sherif, Mohamed id: '67234' last_name: Sherif orcid: https://orcid.org/0000-0002-9927-2203 - first_name: Diego full_name: Moussallem, Diego id: '71635' last_name: Moussallem - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo citation: ama: 'Ahmed AFA, Firmansyah AF, Sherif M, Moussallem D, Ngonga Ngomo A-C. Explainable Integration of Knowledge Graphs Using Large Language Models. In: Natural Language Processing and Information Systems. Springer Nature Switzerland; 2023. doi:10.1007/978-3-031-35320-8_9' apa: Ahmed, A. F. A., Firmansyah, A. F., Sherif, M., Moussallem, D., & Ngonga Ngomo, A.-C. (2023). Explainable Integration of Knowledge Graphs Using Large Language Models. In Natural Language Processing and Information Systems. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-35320-8_9 bibtex: '@inbook{Ahmed_Firmansyah_Sherif_Moussallem_Ngonga Ngomo_2023, place={Cham}, title={Explainable Integration of Knowledge Graphs Using Large Language Models}, DOI={10.1007/978-3-031-35320-8_9}, booktitle={Natural Language Processing and Information Systems}, publisher={Springer Nature Switzerland}, author={Ahmed, Abdullah Fathi Ahmed and Firmansyah, Asep Fajar and Sherif, Mohamed and Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille}, year={2023} }' chicago: 'Ahmed, Abdullah Fathi Ahmed, Asep Fajar Firmansyah, Mohamed Sherif, Diego Moussallem, and Axel-Cyrille Ngonga Ngomo. “Explainable Integration of Knowledge Graphs Using Large Language Models.” In Natural Language Processing and Information Systems. Cham: Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-35320-8_9.' ieee: 'A. F. A. Ahmed, A. F. Firmansyah, M. Sherif, D. Moussallem, and A.-C. Ngonga Ngomo, “Explainable Integration of Knowledge Graphs Using Large Language Models,” in Natural Language Processing and Information Systems, Cham: Springer Nature Switzerland, 2023.' mla: Ahmed, Abdullah Fathi Ahmed, et al. “Explainable Integration of Knowledge Graphs Using Large Language Models.” Natural Language Processing and Information Systems, Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-35320-8_9. short: 'A.F.A. Ahmed, A.F. Firmansyah, M. Sherif, D. Moussallem, A.-C. Ngonga Ngomo, in: Natural Language Processing and Information Systems, Springer Nature Switzerland, Cham, 2023.' date_created: 2023-08-16T08:57:11Z date_updated: 2023-08-16T09:15:42Z department: - _id: '34' doi: 10.1007/978-3-031-35320-8_9 language: - iso: eng place: Cham publication: Natural Language Processing and Information Systems publication_identifier: isbn: - '9783031353192' - '9783031353208' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer Nature Switzerland status: public title: Explainable Integration of Knowledge Graphs Using Large Language Models type: book_chapter user_id: '67234' year: '2023' ... --- _id: '46572' abstract: - lang: eng text: Indonesian is classified as underrepresented in the Natural Language Processing (NLP) field, despite being the tenth most spoken language in the world with 198 million speakers. The paucity of datasets is recognized as the main reason for the slow advancements in NLP research for underrepresented languages. Significant attempts were made in 2020 to address this drawback for Indonesian. The Indonesian Natural Language Understanding (IndoNLU) benchmark was introduced alongside IndoBERT pre-trained language model. The second benchmark, Indonesian Language Evaluation Montage (IndoLEM), was presented in the same year. These benchmarks support several tasks, including Named Entity Recognition (NER). However, all NER datasets are in the public domain and do not contain domain-specific datasets. To alleviate this drawback, we introduce IndQNER, a manually annotated NER benchmark dataset in the religious domain that adheres to a meticulously designed annotation guideline. Since Indonesia has the world’s largest Muslim population, we build the dataset from the Indonesian translation of the Quran. The dataset includes 2475 named entities representing 18 different classes. To assess the annotation quality of IndQNER, we perform experiments with BiLSTM and CRF-based NER, as well as IndoBERT fine-tuning. The results reveal that the first model outperforms the second model achieving 0.98 F1 points. This outcome indicates that IndQNER may be an acceptable evaluation metric for Indonesian NER tasks in the aforementioned domain, widening the research’s domain range. author: - first_name: Ria Hari full_name: Gusmita, Ria Hari last_name: Gusmita - first_name: Asep Fajar full_name: Firmansyah, Asep Fajar last_name: Firmansyah - first_name: Diego full_name: Moussallem, Diego last_name: Moussallem - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille last_name: Ngonga Ngomo citation: ama: 'Gusmita RH, Firmansyah AF, Moussallem D, Ngonga Ngomo A-C. IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran. In: Natural Language Processing and Information Systems. Springer Nature Switzerland; 2023. doi:10.1007/978-3-031-35320-8_12' apa: 'Gusmita, R. H., Firmansyah, A. F., Moussallem, D., & Ngonga Ngomo, A.-C. (2023). IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran. In Natural Language Processing and Information Systems. International Conference on Applications of Natural Language to Information Systems (NLDB) 2023, Derby, UK. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-35320-8_12' bibtex: '@inbook{Gusmita_Firmansyah_Moussallem_Ngonga Ngomo_2023, place={Cham}, title={IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran}, DOI={10.1007/978-3-031-35320-8_12}, booktitle={Natural Language Processing and Information Systems}, publisher={Springer Nature Switzerland}, author={Gusmita, Ria Hari and Firmansyah, Asep Fajar and Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille}, year={2023} }' chicago: 'Gusmita, Ria Hari, Asep Fajar Firmansyah, Diego Moussallem, and Axel-Cyrille Ngonga Ngomo. “IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran.” In Natural Language Processing and Information Systems. Cham: Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-35320-8_12.' ieee: 'R. H. Gusmita, A. F. Firmansyah, D. Moussallem, and A.-C. Ngonga Ngomo, “IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran,” in Natural Language Processing and Information Systems, Cham: Springer Nature Switzerland, 2023.' mla: 'Gusmita, Ria Hari, et al. “IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran.” Natural Language Processing and Information Systems, Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-35320-8_12.' short: 'R.H. Gusmita, A.F. Firmansyah, D. Moussallem, A.-C. Ngonga Ngomo, in: Natural Language Processing and Information Systems, Springer Nature Switzerland, Cham, 2023.' conference: end_date: 2023-06-23 location: Derby, UK name: International Conference on Applications of Natural Language to Information Systems (NLDB) 2023 start_date: 2023-06-21 date_created: 2023-08-17T12:41:45Z date_updated: 2023-08-17T12:52:03Z department: - _id: '574' doi: 10.1007/978-3-031-35320-8_12 language: - iso: eng place: Cham publication: Natural Language Processing and Information Systems publication_identifier: isbn: - '9783031353192' - '9783031353208' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer Nature Switzerland status: public title: 'IndQNER: Named Entity Recognition Benchmark Dataset from the Indonesian Translation of the Quran' type: book_chapter user_id: '76787' year: '2023' ... --- _id: '46867' author: - first_name: Peter full_name: Dieter, Peter id: '88592' last_name: Dieter citation: ama: 'Dieter P. A Regret Policy for the Dynamic Vehicle Routing Problem with Time Windows. In: Lecture Notes in Computer Science. Springer Nature Switzerland; 2023. doi:10.1007/978-3-031-43612-3_14' apa: Dieter, P. (2023). A Regret Policy for the Dynamic Vehicle Routing Problem with Time Windows. In Lecture Notes in Computer Science. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-43612-3_14 bibtex: '@inbook{Dieter_2023, place={Cham}, title={A Regret Policy for the Dynamic Vehicle Routing Problem with Time Windows}, DOI={10.1007/978-3-031-43612-3_14}, booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland}, author={Dieter, Peter}, year={2023} }' chicago: 'Dieter, Peter. “A Regret Policy for the Dynamic Vehicle Routing Problem with Time Windows.” In Lecture Notes in Computer Science. Cham: Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-43612-3_14.' ieee: 'P. Dieter, “A Regret Policy for the Dynamic Vehicle Routing Problem with Time Windows,” in Lecture Notes in Computer Science, Cham: Springer Nature Switzerland, 2023.' mla: Dieter, Peter. “A Regret Policy for the Dynamic Vehicle Routing Problem with Time Windows.” Lecture Notes in Computer Science, Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-43612-3_14. short: 'P. Dieter, in: Lecture Notes in Computer Science, Springer Nature Switzerland, Cham, 2023.' date_created: 2023-09-07T17:46:08Z date_updated: 2023-09-07T17:52:46Z ddc: - '000' department: - _id: '277' doi: 10.1007/978-3-031-43612-3_14 has_accepted_license: '1' language: - iso: eng place: Cham publication: Lecture Notes in Computer Science publication_identifier: isbn: - '9783031436116' - '9783031436123' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer Nature Switzerland status: public title: A Regret Policy for the Dynamic Vehicle Routing Problem with Time Windows type: book_chapter user_id: '51811' year: '2023' ... --- _id: '47421' abstract: - lang: eng text: Class expression learning in description logics has long been regarded as an iterative search problem in an infinite conceptual space. Each iteration of the search process invokes a reasoner and a heuristic function. The reasoner finds the instances of the current expression, and the heuristic function computes the information gain and decides on the next step to be taken. As the size of the background knowledge base grows, search-based approaches for class expression learning become prohibitively slow. Current neural class expression synthesis (NCES) approaches investigate the use of neural networks for class expression learning in the attributive language with complement (ALC). While they show significant improvements over search-based approaches in runtime and quality of the computed solutions, they rely on the availability of pretrained embeddings for the input knowledge base. Moreover, they are not applicable to ontologies in more expressive description logics. In this paper, we propose a novel NCES approach which extends the state of the art to the description logic ALCHIQ(D). Our extension, dubbed NCES2, comes with an improved training data generator and does not require pretrained embeddings for the input knowledge base as both the embedding model and the class expression synthesizer are trained jointly. Empirical results on benchmark datasets suggest that our approach inherits the scalability capability of current NCES instances with the additional advantage that it supports more complex learning problems. NCES2 achieves the highest performance overall when compared to search-based approaches and to its predecessor NCES. We provide our source code, datasets, and pretrained models at https://github.com/dice-group/NCES2. author: - first_name: N'Dah Jean full_name: Kouagou, N'Dah Jean id: '87189' last_name: Kouagou - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Caglar full_name: Demir, Caglar id: '43817' last_name: Demir - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo citation: ama: 'Kouagou NJ, Heindorf S, Demir C, Ngonga Ngomo A-C. Neural Class Expression Synthesis in ALCHIQ(D). In: Machine Learning and Knowledge Discovery in Databases: Research Track. Springer Nature Switzerland; 2023. doi:10.1007/978-3-031-43421-1_12' apa: 'Kouagou, N. J., Heindorf, S., Demir, C., & Ngonga Ngomo, A.-C. (2023). Neural Class Expression Synthesis in ALCHIQ(D). In Machine Learning and Knowledge Discovery in Databases: Research Track. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Turin. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-43421-1_12' bibtex: '@inbook{Kouagou_Heindorf_Demir_Ngonga Ngomo_2023, place={Cham}, title={Neural Class Expression Synthesis in ALCHIQ(D)}, DOI={10.1007/978-3-031-43421-1_12}, booktitle={Machine Learning and Knowledge Discovery in Databases: Research Track}, publisher={Springer Nature Switzerland}, author={Kouagou, N’Dah Jean and Heindorf, Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2023} }' chicago: 'Kouagou, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “Neural Class Expression Synthesis in ALCHIQ(D).” In Machine Learning and Knowledge Discovery in Databases: Research Track. Cham: Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-43421-1_12.' ieee: 'N. J. Kouagou, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Neural Class Expression Synthesis in ALCHIQ(D),” in Machine Learning and Knowledge Discovery in Databases: Research Track, Cham: Springer Nature Switzerland, 2023.' mla: 'Kouagou, N’Dah Jean, et al. “Neural Class Expression Synthesis in ALCHIQ(D).” Machine Learning and Knowledge Discovery in Databases: Research Track, Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-43421-1_12.' short: 'N.J. Kouagou, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: Machine Learning and Knowledge Discovery in Databases: Research Track, Springer Nature Switzerland, Cham, 2023.' conference: end_date: 2023-09-22 location: Turin name: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases start_date: 2023-09-18 date_created: 2023-09-25T13:42:01Z date_updated: 2023-11-21T09:20:31Z department: - _id: '760' - _id: '574' doi: 10.1007/978-3-031-43421-1_12 language: - iso: eng place: Cham publication: 'Machine Learning and Knowledge Discovery in Databases: Research Track' publication_identifier: isbn: - '9783031434204' - '9783031434211' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer Nature Switzerland status: public title: Neural Class Expression Synthesis in ALCHIQ(D) type: book_chapter user_id: '11871' year: '2023' ... --- _id: '47953' author: - first_name: Jaroslaw full_name: Kornowicz, Jaroslaw id: '44029' last_name: Kornowicz - first_name: Kirsten full_name: Thommes, Kirsten id: '72497' last_name: Thommes citation: ama: Kornowicz J, Thommes K. Aggregating Human Domain Knowledge for Feature Ranking. Artificial Intelligence in HCI. Published online 2023. doi:10.1007/978-3-031-35891-3_7 apa: Kornowicz, J., & Thommes, K. (2023). Aggregating Human Domain Knowledge for Feature Ranking. Artificial Intelligence in HCI. https://doi.org/10.1007/978-3-031-35891-3_7 bibtex: '@article{Kornowicz_Thommes_2023, title={Aggregating Human Domain Knowledge for Feature Ranking}, DOI={10.1007/978-3-031-35891-3_7}, journal={Artificial Intelligence in HCI}, publisher={Springer Nature Switzerland}, author={Kornowicz, Jaroslaw and Thommes, Kirsten}, year={2023} }' chicago: Kornowicz, Jaroslaw, and Kirsten Thommes. “Aggregating Human Domain Knowledge for Feature Ranking.” Artificial Intelligence in HCI, 2023. https://doi.org/10.1007/978-3-031-35891-3_7. ieee: 'J. Kornowicz and K. Thommes, “Aggregating Human Domain Knowledge for Feature Ranking,” Artificial Intelligence in HCI, 2023, doi: 10.1007/978-3-031-35891-3_7.' mla: Kornowicz, Jaroslaw, and Kirsten Thommes. “Aggregating Human Domain Knowledge for Feature Ranking.” Artificial Intelligence in HCI, Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-35891-3_7. short: J. Kornowicz, K. Thommes, Artificial Intelligence in HCI (2023). date_created: 2023-10-11T08:01:00Z date_updated: 2023-12-05T10:15:37Z department: - _id: '184' - _id: '178' doi: 10.1007/978-3-031-35891-3_7 language: - iso: eng project: - _id: '125' name: 'TRR 318 - C2: TRR 318 - Subproject C2' publication: Artificial Intelligence in HCI publication_identifier: isbn: - '9783031358906' - '9783031358913' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer Nature Switzerland status: public title: Aggregating Human Domain Knowledge for Feature Ranking type: journal_article user_id: '42933' year: '2023' ... --- _id: '50479' abstract: - lang: eng text: Verifying assertions is an essential part of creating and maintaining knowledge graphs. Most often, this task cannot be carried out manually due to the sheer size of modern knowledge graphs. Hence, automatic fact-checking approaches have been proposed over the last decade. These approaches aim to compute automatically whether a given assertion is correct or incorrect. However, most fact-checking approaches are binary classifiers that fail to consider the volatility of some assertions, i.e., the fact that such assertions are only valid at certain times or for specific time intervals. Moreover, the few approaches able to predict when an assertion was valid (i.e., time-point prediction approaches) rely on manual feature engineering. This paper presents TEMPORALFC, a temporal fact-checking approach that uses multiple sources of background knowledge to assess the veracity and temporal validity of a given assertion. We evaluate TEMPORALFC on two datasets and compare it to the state of the art in fact-checking and time-point prediction. Our results suggest that TEMPORALFC outperforms the state of the art on the fact-checking task by 0.13 to 0.15 in terms of Area Under the Receiver Operating Characteristic curve and on the time-point prediction task by 0.25 to 0.27 in terms of Mean Reciprocal Rank. Our code is open-source and can be found at https://github.com/dice-group/TemporalFC. author: - first_name: Umair full_name: Qudus, Umair last_name: Qudus - first_name: Michael full_name: Röder, Michael last_name: Röder - first_name: Sabrina full_name: Kirrane, Sabrina last_name: Kirrane - first_name: Axel-Cyrille Ngonga full_name: Ngomo, Axel-Cyrille Ngonga last_name: Ngomo citation: ama: 'Qudus U, Röder M, Kirrane S, Ngomo A-CN. TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs. In: R. Payne T, Presutti V, Qi G, et al., eds. The Semantic Web – ISWC 2023. Vol 14265. Lecture Notes in Computer Science. Springer, Cham; 2023:465–483. doi:10.1007/978-3-031-47240-4_25' apa: 'Qudus, U., Röder, M., Kirrane, S., & Ngomo, A.-C. N. (2023). TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs. In T. R. Payne, V. Presutti, G. Qi, M. Poveda-Villalón, G. Stoilos, L. Hollink, Z. Kaoudi, G. Cheng, & J. Li (Eds.), The Semantic Web – ISWC 2023 (Vol. 14265, pp. 465–483). Springer, Cham. https://doi.org/10.1007/978-3-031-47240-4_25' bibtex: '@inproceedings{Qudus_Röder_Kirrane_Ngomo_2023, place={Cham}, series={ Lecture Notes in Computer Science}, title={TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs}, volume={14265}, DOI={10.1007/978-3-031-47240-4_25}, booktitle={The Semantic Web – ISWC 2023}, publisher={Springer, Cham}, author={Qudus, Umair and Röder, Michael and Kirrane, Sabrina and Ngomo, Axel-Cyrille Ngonga}, editor={R. Payne, Terry and Presutti, Valentina and Qi, Guilin and Poveda-Villalón, María and Stoilos, Giorgos and Hollink, Laura and Kaoudi, Zoi and Cheng, Gong and Li, Juanzi}, year={2023}, pages={465–483}, collection={ Lecture Notes in Computer Science} }' chicago: 'Qudus, Umair, Michael Röder, Sabrina Kirrane, and Axel-Cyrille Ngonga Ngomo. “TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs.” In The Semantic Web – ISWC 2023, edited by Terry R. Payne, Valentina Presutti, Guilin Qi, María Poveda-Villalón, Giorgos Stoilos, Laura Hollink, Zoi Kaoudi, Gong Cheng, and Juanzi Li, 14265:465–483. Lecture Notes in Computer Science. Cham: Springer, Cham, 2023. https://doi.org/10.1007/978-3-031-47240-4_25.' ieee: 'U. Qudus, M. Röder, S. Kirrane, and A.-C. N. Ngomo, “TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs,” in The Semantic Web – ISWC 2023, Athens, Greece, 2023, vol. 14265, pp. 465–483, doi: 10.1007/978-3-031-47240-4_25.' mla: 'Qudus, Umair, et al. “TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs.” The Semantic Web – ISWC 2023, edited by Terry R. Payne et al., vol. 14265, Springer, Cham, 2023, pp. 465–483, doi:10.1007/978-3-031-47240-4_25.' short: 'U. Qudus, M. Röder, S. Kirrane, A.-C.N. Ngomo, in: T. R. Payne, V. Presutti, G. Qi, M. Poveda-Villalón, G. Stoilos, L. Hollink, Z. Kaoudi, G. Cheng, J. Li (Eds.), The Semantic Web – ISWC 2023, Springer, Cham, Cham, 2023, pp. 465–483.' conference: end_date: 2023-11-10 location: Athens, Greece name: The Semantic Web – ISWC 2023 start_date: 2023-11-06 date_created: 2024-01-13T11:22:15Z date_updated: 2024-01-13T11:48:28Z ddc: - '006' department: - _id: '34' doi: 10.1007/978-3-031-47240-4_25 editor: - first_name: Terry full_name: R. Payne, Terry last_name: R. Payne - first_name: Valentina full_name: Presutti, Valentina last_name: Presutti - first_name: Guilin full_name: Qi, Guilin last_name: Qi - first_name: María full_name: Poveda-Villalón, María last_name: Poveda-Villalón - first_name: Giorgos full_name: Stoilos, Giorgos last_name: Stoilos - first_name: Laura full_name: Hollink, Laura last_name: Hollink - first_name: Zoi full_name: Kaoudi, Zoi last_name: Kaoudi - first_name: Gong full_name: Cheng, Gong last_name: Cheng - first_name: Juanzi full_name: Li, Juanzi last_name: Li file: - access_level: closed content_type: application/pdf creator: uqudus date_created: 2024-01-13T11:25:48Z date_updated: 2024-01-13T11:25:48Z file_id: '50480' file_name: ISWC 2023 TemporalFC-A Temporal Fact Checking approach over Knowledge Graphs.pdf file_size: 1944818 relation: main_file success: 1 file_date_updated: 2024-01-13T11:25:48Z has_accepted_license: '1' intvolume: ' 14265' jel: - C keyword: - temporal fact checking · ensemble learning · transfer learning · time-point prediction · temporal knowledge graphs language: - iso: eng license: https://creativecommons.org/publicdomain/zero/1.0/ page: 465–483 place: Cham project: - _id: '410' grant_number: '860801' name: 'KnowGraphs: KnowGraphs: Knowledge Graphs at Scale' publication: The Semantic Web – ISWC 2023 publication_identifier: isbn: - '9783031472398' - '9783031472404' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer, Cham series_title: ' Lecture Notes in Computer Science' status: public title: 'TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs' type: conference user_id: '83392' volume: 14265 year: '2023' ... --- _id: '46191' author: - first_name: Christoph full_name: Alt, Christoph id: '100625' last_name: Alt - first_name: Tobias full_name: Kenter, Tobias id: '3145' last_name: Kenter - first_name: Sara full_name: Faghih-Naini, Sara last_name: Faghih-Naini - first_name: Jennifer full_name: Faj, Jennifer id: '78722' last_name: Faj - first_name: Jan-Oliver full_name: Opdenhövel, Jan-Oliver last_name: Opdenhövel - first_name: Christian full_name: Plessl, Christian id: '16153' last_name: Plessl orcid: 0000-0001-5728-9982 - first_name: Vadym full_name: Aizinger, Vadym last_name: Aizinger - first_name: Jan full_name: Hönig, Jan last_name: Hönig - first_name: Harald full_name: Köstler, Harald last_name: Köstler citation: ama: 'Alt C, Kenter T, Faghih-Naini S, et al. Shallow Water DG Simulations on FPGAs: Design and Comparison of a Novel Code Generation Pipeline. In: Lecture Notes in Computer Science. Springer Nature Switzerland; 2023. doi:10.1007/978-3-031-32041-5_5' apa: 'Alt, C., Kenter, T., Faghih-Naini, S., Faj, J., Opdenhövel, J.-O., Plessl, C., Aizinger, V., Hönig, J., & Köstler, H. (2023). Shallow Water DG Simulations on FPGAs: Design and Comparison of a Novel Code Generation Pipeline. In Lecture Notes in Computer Science. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-32041-5_5' bibtex: '@inbook{Alt_Kenter_Faghih-Naini_Faj_Opdenhövel_Plessl_Aizinger_Hönig_Köstler_2023, place={Cham}, title={Shallow Water DG Simulations on FPGAs: Design and Comparison of a Novel Code Generation Pipeline}, DOI={10.1007/978-3-031-32041-5_5}, booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland}, author={Alt, Christoph and Kenter, Tobias and Faghih-Naini, Sara and Faj, Jennifer and Opdenhövel, Jan-Oliver and Plessl, Christian and Aizinger, Vadym and Hönig, Jan and Köstler, Harald}, year={2023} }' chicago: 'Alt, Christoph, Tobias Kenter, Sara Faghih-Naini, Jennifer Faj, Jan-Oliver Opdenhövel, Christian Plessl, Vadym Aizinger, Jan Hönig, and Harald Köstler. “Shallow Water DG Simulations on FPGAs: Design and Comparison of a Novel Code Generation Pipeline.” In Lecture Notes in Computer Science. Cham: Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-32041-5_5.' ieee: 'C. Alt et al., “Shallow Water DG Simulations on FPGAs: Design and Comparison of a Novel Code Generation Pipeline,” in Lecture Notes in Computer Science, Cham: Springer Nature Switzerland, 2023.' mla: 'Alt, Christoph, et al. “Shallow Water DG Simulations on FPGAs: Design and Comparison of a Novel Code Generation Pipeline.” Lecture Notes in Computer Science, Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-32041-5_5.' short: 'C. Alt, T. Kenter, S. Faghih-Naini, J. Faj, J.-O. Opdenhövel, C. Plessl, V. Aizinger, J. Hönig, H. Köstler, in: Lecture Notes in Computer Science, Springer Nature Switzerland, Cham, 2023.' date_created: 2023-07-28T09:53:21Z date_updated: 2024-01-22T09:58:49Z department: - _id: '27' - _id: '518' doi: 10.1007/978-3-031-32041-5_5 language: - iso: eng place: Cham project: - _id: '52' name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing' publication: Lecture Notes in Computer Science publication_identifier: isbn: - '9783031320408' - '9783031320415' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer Nature Switzerland quality_controlled: '1' status: public title: 'Shallow Water DG Simulations on FPGAs: Design and Comparison of a Novel Code Generation Pipeline' type: book_chapter user_id: '3145' year: '2023' ... --- _id: '51373' author: - first_name: Jonas Manuel full_name: Hanselle, Jonas Manuel id: '43980' last_name: Hanselle orcid: 0000-0002-1231-4985 - first_name: Johannes full_name: Fürnkranz, Johannes last_name: Fürnkranz - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Hanselle JM, Fürnkranz J, Hüllermeier E. Probabilistic Scoring Lists for Interpretable Machine Learning. In: 26th International Conference on Discovery Science . Vol 14050. Lecture Notes in Computer Science. Springer Nature Switzerland; 2023:189-203. doi:10.1007/978-3-031-45275-8_13' apa: Hanselle, J. M., Fürnkranz, J., & Hüllermeier, E. (2023). Probabilistic Scoring Lists for Interpretable Machine Learning. 26th International Conference on Discovery Science , 14050, 189–203. https://doi.org/10.1007/978-3-031-45275-8_13 bibtex: '@inproceedings{Hanselle_Fürnkranz_Hüllermeier_2023, place={Cham}, series={Lecture Notes in Computer Science}, title={Probabilistic Scoring Lists for Interpretable Machine Learning}, volume={14050}, DOI={10.1007/978-3-031-45275-8_13}, booktitle={26th International Conference on Discovery Science }, publisher={Springer Nature Switzerland}, author={Hanselle, Jonas Manuel and Fürnkranz, Johannes and Hüllermeier, Eyke}, year={2023}, pages={189–203}, collection={Lecture Notes in Computer Science} }' chicago: 'Hanselle, Jonas Manuel, Johannes Fürnkranz, and Eyke Hüllermeier. “Probabilistic Scoring Lists for Interpretable Machine Learning.” In 26th International Conference on Discovery Science , 14050:189–203. Lecture Notes in Computer Science. Cham: Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-45275-8_13.' ieee: 'J. M. Hanselle, J. Fürnkranz, and E. Hüllermeier, “Probabilistic Scoring Lists for Interpretable Machine Learning,” in 26th International Conference on Discovery Science , Porto, 2023, vol. 14050, pp. 189–203, doi: 10.1007/978-3-031-45275-8_13.' mla: Hanselle, Jonas Manuel, et al. “Probabilistic Scoring Lists for Interpretable Machine Learning.” 26th International Conference on Discovery Science , vol. 14050, Springer Nature Switzerland, 2023, pp. 189–203, doi:10.1007/978-3-031-45275-8_13. short: 'J.M. Hanselle, J. Fürnkranz, E. Hüllermeier, in: 26th International Conference on Discovery Science , Springer Nature Switzerland, Cham, 2023, pp. 189–203.' conference: end_date: 2021-10-11 location: Porto name: '26th International Conference on Discovery Science ' start_date: 2023-10-9 date_created: 2024-02-18T11:05:55Z date_updated: 2024-02-26T08:41:49Z doi: 10.1007/978-3-031-45275-8_13 intvolume: ' 14050' language: - iso: eng page: 189-203 place: Cham publication: '26th International Conference on Discovery Science ' publication_identifier: isbn: - '9783031452741' - '9783031452758' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer Nature Switzerland series_title: Lecture Notes in Computer Science status: public title: Probabilistic Scoring Lists for Interpretable Machine Learning type: conference user_id: '54779' volume: 14050 year: '2023' ...