[{"oa":"1","date_updated":"2025-09-11T09:30:28Z","author":[{"first_name":"Umair","last_name":"Qudus","orcid":"0000-0001-6714-8729","full_name":"Qudus, Umair","id":"83392"},{"first_name":"Michael","last_name":"Röder","orcid":"https://orcid.org/0000-0002-8609-8277","full_name":"Röder, Michael","id":"67199"},{"last_name":"Saleem","full_name":"Saleem, Muhammad","first_name":"Muhammad"},{"id":"65716","full_name":"Ngonga Ngomo, Axel-Cyrille","last_name":"Ngonga Ngomo","first_name":"Axel-Cyrille"}],"volume":58,"main_file_link":[{"open_access":"1","url":"https://dl.acm.org/doi/pdf/10.1145/3749838"}],"doi":"10.1145/3749838","publication_status":"published","publication_identifier":{"issn":["0360-0300","1557-7341"]},"has_accepted_license":"1","citation":{"mla":"Qudus, Umair, et al. “Fact Checking Knowledge Graphs -- A Survey.” <i>ACM Computing Surveys</i>, vol. 58, 3749838, Association for Computing Machinery (ACM), 2025, doi:<a href=\"https://doi.org/10.1145/3749838\">10.1145/3749838</a>.","short":"U. Qudus, M. Röder, M. Saleem, A.-C. Ngonga Ngomo, ACM Computing Surveys 58 (2025).","bibtex":"@article{Qudus_Röder_Saleem_Ngonga Ngomo_2025, title={Fact Checking Knowledge Graphs -- A Survey}, volume={58}, DOI={<a href=\"https://doi.org/10.1145/3749838\">10.1145/3749838</a>}, number={3749838}, journal={ACM Computing Surveys}, publisher={Association for Computing Machinery (ACM)}, author={Qudus, Umair and Röder, Michael and Saleem, Muhammad and Ngonga Ngomo, Axel-Cyrille}, year={2025} }","apa":"Qudus, U., Röder, M., Saleem, M., &#38; Ngonga Ngomo, A.-C. (2025). Fact Checking Knowledge Graphs -- A Survey. <i>ACM Computing Surveys</i>, <i>58</i>, Article 3749838. <a href=\"https://doi.org/10.1145/3749838\">https://doi.org/10.1145/3749838</a>","ama":"Qudus U, Röder M, Saleem M, Ngonga Ngomo A-C. Fact Checking Knowledge Graphs -- A Survey. <i>ACM Computing Surveys</i>. 2025;58. doi:<a href=\"https://doi.org/10.1145/3749838\">10.1145/3749838</a>","chicago":"Qudus, Umair, Michael Röder, Muhammad Saleem, and Axel-Cyrille Ngonga Ngomo. “Fact Checking Knowledge Graphs -- A Survey.” <i>ACM Computing Surveys</i> 58 (2025). <a href=\"https://doi.org/10.1145/3749838\">https://doi.org/10.1145/3749838</a>.","ieee":"U. Qudus, M. Röder, M. Saleem, and A.-C. Ngonga Ngomo, “Fact Checking Knowledge Graphs -- A Survey,” <i>ACM Computing Surveys</i>, vol. 58, Art. no. 3749838, 2025, doi: <a href=\"https://doi.org/10.1145/3749838\">10.1145/3749838</a>."},"intvolume":"        58","_id":"61123","user_id":"83392","department":[{"_id":"574"}],"article_type":"original","article_number":"3749838","file_date_updated":"2025-09-11T09:26:29Z","popular_science":"1","type":"journal_article","status":"public","publisher":"Association for Computing Machinery (ACM)","date_created":"2025-09-03T15:46:43Z","title":"Fact Checking Knowledge Graphs -- A Survey","quality_controlled":"1","year":"2025","external_id":{"unknown":["10.1145/3749838"]},"ddc":["006"],"keyword":["fact checking","knowledge graphs","fact-checkers","check worthiness","evidence retrieval","trust","veracity."],"language":[{"iso":"eng"}],"publication":"ACM Computing Surveys","abstract":[{"text":"<jats:p>Knowledge graphs are used by a growing number of applications to represent structured data. Hence, evaluating the veracity of assertions in knowledge graphs—dubbed fact checking—is currently a challenge of growing importance. However, manual fact checking is commonly impractical due to the sheer size of knowledge graphs. This paper is a systematic survey of recent works on automatic fact checking with a focus on knowledge graphs. We present recent fact-checking approaches, the varied sources they use as background knowledge, and the features they rely upon. Finally, we draw conclusions pertaining to possible future research directions in fact checking knowledge graphs.</jats:p>","lang":"eng"}],"file":[{"date_created":"2025-09-11T09:26:29Z","creator":"uqudus","date_updated":"2025-09-11T09:26:29Z","access_level":"closed","file_id":"61195","file_name":"3749838.pdf","file_size":1062387,"content_type":"application/pdf","relation":"main_file","success":1}]},{"language":[{"iso":"eng"}],"keyword":["Stance Classification","Few-shot in-context learning","Pre-trained large language models"],"ddc":["006"],"file":[{"content_type":"application/pdf","relation":"main_file","success":1,"date_created":"2024-11-11T13:24:19Z","creator":"uqudus","date_updated":"2024-11-11T13:24:19Z","access_level":"closed","file_id":"56984","file_name":"public.pdf","file_size":531579}],"abstract":[{"lang":"eng","text":"Detecting the veracity of a statement automatically is a challenge the world is grappling with due to the vast amount of data spread across the web. Verifying a given claim typically entails validating it within the framework of supporting evidence like a retrieved piece of text. Classifying the stance of the text with respect to the claim is called stance classification. Despite advancements in automated fact-checking, most systems still rely on a substantial quantity of labeled training data, which can be costly. In this work, we avoid the costly training or fine-tuning of models by reusing pre-trained large language models together with few-shot in-context learning. Since we do not train any model, our approach ExPrompt is lightweight, demands fewer resources than other stance classification methods and can serve as a modern baseline for future developments. At the same time, our evaluation shows that our approach is able to outperform former state-of-the-art stance classification approaches regarding accuracy by at least 2 percent. Our scripts and data used in this paper are available at https://github.com/dice-group/ExPrompt."}],"publication":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","title":"ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification","date_created":"2024-11-11T13:15:25Z","publisher":"ACM","year":"2024","quality_controlled":"1","file_date_updated":"2024-11-11T13:24:19Z","user_id":"83392","_id":"56983","project":[{"name":"NEBULA: Nutzerzentrierte KI-basierte Erkennung von Fake-News und Fehlinformationen","_id":"412"}],"status":"public","popular_science":"1","type":"conference","conference":{"location":"Boise, ID, USA","end_date":"2024-10-25","start_date":"2024-10-21","name":"CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management"},"doi":"10.1145/3627673.3679923","main_file_link":[{"url":"https://dl.acm.org/doi/10.1145/3627673.3679923"}],"volume":9,"author":[{"id":"83392","full_name":"Qudus, Umair","orcid":"0000-0001-6714-8729","last_name":"Qudus","first_name":"Umair"},{"first_name":"Michael","orcid":"https://orcid.org/0000-0002-8609-8277","last_name":"Röder","id":"67199","full_name":"Röder, Michael"},{"first_name":"Daniel","last_name":"Vollmers","full_name":"Vollmers, Daniel"},{"first_name":"Axel-Cyrille","id":"65716","full_name":"Ngonga Ngomo, Axel-Cyrille","last_name":"Ngonga Ngomo"}],"date_updated":"2025-09-11T09:49:07Z","page":"3994 - 3999","intvolume":"         9","citation":{"apa":"Qudus, U., Röder, M., Vollmers, D., &#38; Ngonga Ngomo, A.-C. (2024). ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification. <i>Proceedings of the 33rd ACM International Conference on Information and Knowledge Management</i>, <i>9</i>, 3994–3999. <a href=\"https://doi.org/10.1145/3627673.3679923\">https://doi.org/10.1145/3627673.3679923</a>","short":"U. Qudus, M. Röder, D. Vollmers, A.-C. Ngonga Ngomo, in: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, ACM, 2024, pp. 3994–3999.","mla":"Qudus, Umair, et al. “ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification.” <i>Proceedings of the 33rd ACM International Conference on Information and Knowledge Management</i>, vol. 9, ACM, 2024, pp. 3994–99, doi:<a href=\"https://doi.org/10.1145/3627673.3679923\">10.1145/3627673.3679923</a>.","bibtex":"@inproceedings{Qudus_Röder_Vollmers_Ngonga Ngomo_2024, title={ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification}, volume={9}, DOI={<a href=\"https://doi.org/10.1145/3627673.3679923\">10.1145/3627673.3679923</a>}, booktitle={Proceedings of the 33rd ACM International Conference on Information and Knowledge Management}, publisher={ACM}, author={Qudus, Umair and Röder, Michael and Vollmers, Daniel and Ngonga Ngomo, Axel-Cyrille}, year={2024}, pages={3994–3999} }","ama":"Qudus U, Röder M, Vollmers D, Ngonga Ngomo A-C. ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification. In: <i>Proceedings of the 33rd ACM International Conference on Information and Knowledge Management</i>. Vol 9. ACM; 2024:3994-3999. doi:<a href=\"https://doi.org/10.1145/3627673.3679923\">10.1145/3627673.3679923</a>","chicago":"Qudus, Umair, Michael Röder, Daniel Vollmers, and Axel-Cyrille Ngonga Ngomo. “ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification.” In <i>Proceedings of the 33rd ACM International Conference on Information and Knowledge Management</i>, 9:3994–99. ACM, 2024. <a href=\"https://doi.org/10.1145/3627673.3679923\">https://doi.org/10.1145/3627673.3679923</a>.","ieee":"U. Qudus, M. Röder, D. Vollmers, and A.-C. Ngonga Ngomo, “ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification,” in <i>Proceedings of the 33rd ACM International Conference on Information and Knowledge Management</i>, Boise, ID, USA, 2024, vol. 9, pp. 3994–3999, doi: <a href=\"https://doi.org/10.1145/3627673.3679923\">10.1145/3627673.3679923</a>."},"publication_identifier":{"isbn":["79-8-4007-0436-9/24/10"]},"has_accepted_license":"1","publication_status":"published"},{"quality_controlled":"1","corporate_editor":["Mehwish Alam"],"year":"2024","date_created":"2024-11-19T14:12:49Z","title":"FaVEL: Fact Validation Ensemble Learning","publication":"EKAW 2024","file":[{"date_created":"2024-11-19T14:14:14Z","creator":"uqudus","date_updated":"2024-11-19T14:14:14Z","access_level":"closed","file_id":"57241","file_name":"favel.pdf","file_size":190661,"content_type":"application/pdf","relation":"main_file","success":1}],"abstract":[{"lang":"eng","text":"Validating assertions before adding them to a knowledge graph is an essential part of its creation and maintenance. Due to the sheer size of knowledge graphs, automatic fact-checking approaches have been developed. These approaches rely on reference knowledge to decide whether a given assertion is correct. Recent hybrid approaches achieve good results by including several knowledge sources. However, it is often impractical to provide a sheer quantity of textual knowledge or generate embedding models to leverage these hybrid approaches. We present FaVEL, an approach that uses algorithm selection and ensemble learning to amalgamate several existing fact-checking approaches that rely solely on a reference knowledge graph and, hence, use fewer resources than current hybrid approaches. For our evaluation, we create updated versions of two existing datasets and a new dataset dubbed FaVEL-DS. Our evaluation compares our approach to 15 fact-checking approaches—including the state-of-the-art approach HybridFC—on 3 datasets. Our results demonstrate that FaVEL outperforms all other approaches significantly by at least 0.04 in terms of the area under the ROC curve. Our source code, datasets, and evaluation results are open-source and can be found at https://github.com/dice-group/favel."}],"language":[{"iso":"eng"}],"keyword":["fact checking","ensemble learning","transfer learning","knowledge management."],"ddc":["600"],"has_accepted_license":"1","citation":{"short":"U. Qudus, M. Röder, F.L. Tatkeu Pekarou, A.A. Morim da Silva, A.-C. Ngonga Ngomo, in: M. Rospocher, Mehwish Alam (Eds.), EKAW 2024, 2024.","mla":"Qudus, Umair, et al. “FaVEL: Fact Validation Ensemble Learning.” <i>EKAW 2024</i>, edited by Marco Rospocher and Mehwish Alam, 2024.","bibtex":"@inproceedings{Qudus_Röder_Tatkeu Pekarou_Morim da Silva_Ngonga Ngomo_2024, title={FaVEL: Fact Validation Ensemble Learning}, booktitle={EKAW 2024}, author={Qudus, Umair and Röder, Michael and Tatkeu Pekarou, Franck Lionel and Morim da Silva, Ana Alexandra and Ngonga Ngomo, Axel-Cyrille}, editor={Rospocher, Marco and Mehwish Alam}, year={2024} }","apa":"Qudus, U., Röder, M., Tatkeu Pekarou, F. L., Morim da Silva, A. A., &#38; Ngonga Ngomo, A.-C. (2024). FaVEL: Fact Validation Ensemble Learning. In M. Rospocher &#38; Mehwish Alam (Eds.), <i>EKAW 2024</i>.","ama":"Qudus U, Röder M, Tatkeu Pekarou FL, Morim da Silva AA, Ngonga Ngomo A-C. FaVEL: Fact Validation Ensemble Learning. In: Rospocher M, Mehwish Alam, eds. <i>EKAW 2024</i>. ; 2024.","ieee":"U. Qudus, M. Röder, F. L. Tatkeu Pekarou, A. A. Morim da Silva, and A.-C. Ngonga Ngomo, “FaVEL: Fact Validation Ensemble Learning,” in <i>EKAW 2024</i>, Amsterdam, Netherlands, 2024.","chicago":"Qudus, Umair, Michael Röder, Franck Lionel Tatkeu Pekarou, Ana Alexandra Morim da Silva, and Axel-Cyrille Ngonga Ngomo. “FaVEL: Fact Validation Ensemble Learning.” In <i>EKAW 2024</i>, edited by Marco Rospocher and Mehwish Alam, 2024."},"author":[{"first_name":"Umair","last_name":"Qudus","orcid":"0000-0001-6714-8729","id":"83392","full_name":"Qudus, Umair"},{"first_name":"Michael","full_name":"Röder, Michael","id":"67199","orcid":"https://orcid.org/0000-0002-8609-8277","last_name":"Röder"},{"first_name":"Franck Lionel","full_name":"Tatkeu Pekarou, Franck Lionel","last_name":"Tatkeu Pekarou"},{"last_name":"Morim da Silva","id":"72108","full_name":"Morim da Silva, Ana Alexandra","first_name":"Ana Alexandra"},{"first_name":"Axel-Cyrille","id":"65716","full_name":"Ngonga Ngomo, Axel-Cyrille","last_name":"Ngonga Ngomo"}],"date_updated":"2025-09-11T09:48:12Z","conference":{"location":"Amsterdam, Netherlands","end_date":"2024-11-28","start_date":"2024-11-26","name":"24th International Conference on Knowledge Engineering and Knowledge Management"},"type":"conference","popular_science":"1","status":"public","editor":[{"full_name":"Rospocher, Marco","last_name":"Rospocher","first_name":"Marco"}],"department":[{"_id":"34"}],"user_id":"83392","_id":"57240","project":[{"name":"NEBULA: Nutzerzentrierte KI-basierte Erkennung von Fake-News und Fehlinformationen","_id":"412"},{"name":"SAIL: SAIL - Nachhaltiger Lebenszyklus von intelligenten soziotechnischen Systemen","_id":"285"},{"_id":"410","name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale"}],"file_date_updated":"2024-11-19T14:14:14Z"},{"editor":[{"last_name":"R. Payne","full_name":"R. Payne, Terry","first_name":"Terry"},{"full_name":"Presutti, Valentina","last_name":"Presutti","first_name":"Valentina"},{"first_name":"Guilin","last_name":"Qi","full_name":"Qi, Guilin"},{"last_name":"Poveda-Villalónt","full_name":"Poveda-Villalónt, María","first_name":"María"},{"full_name":"Stoilos, Giorgos","last_name":"Stoilos","first_name":"Giorgos"},{"first_name":"Laura","last_name":"Hollink","full_name":"Hollink, Laura"},{"first_name":"Zoi","last_name":"Kaoudi","full_name":"Kaoudi, Zoi"},{"first_name":"Gong","full_name":"Cheng, Gong","last_name":"Cheng"},{"last_name":"Li","full_name":"Li, Juanzi","first_name":"Juanzi"}],"status":"public","type":"conference","popular_science":"1","file_date_updated":"2025-09-11T09:33:14Z","_id":"50796","series_title":"Lecture Notes in Computer Science","user_id":"83392","place":"Cham","citation":{"ama":"Qudus U, Röder M, Kirrane S, Ngonga Ngomo A-C. TemporalFC: A Temporal Fact Checking approach over Knowledge Graphs. In: R. Payne T, Presutti V, Qi G, et al., eds. <i>The Semantic Web – ISWC 2023</i>. Vol 14265. Lecture Notes in Computer Science. Springer International Publishing; 2023:465–483. doi:<a href=\"https://doi.org/10.1007/978-3-031-47240-4_25\">10.1007/978-3-031-47240-4_25</a>","ieee":"U. Qudus, M. Röder, S. Kirrane, and A.-C. Ngonga Ngomo, “TemporalFC: A Temporal Fact Checking approach over Knowledge Graphs,” in <i>The Semantic Web – ISWC 2023</i>, 2023, vol. 14265, pp. 465–483, doi: <a href=\"https://doi.org/10.1007/978-3-031-47240-4_25\">10.1007/978-3-031-47240-4_25</a>.","chicago":"Qudus, Umair, Michael Röder, Sabrina Kirrane, and Axel-Cyrille Ngonga Ngomo. “TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs.” In <i>The Semantic Web – ISWC 2023</i>, edited by Terry R. Payne, Valentina Presutti, Guilin Qi, María Poveda-Villalónt, Giorgos Stoilos, Laura Hollink, Zoi Kaoudi, Gong Cheng, and Juanzi Li, 14265:465–483. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2023. <a href=\"https://doi.org/10.1007/978-3-031-47240-4_25\">https://doi.org/10.1007/978-3-031-47240-4_25</a>.","apa":"Qudus, U., Röder, M., Kirrane, S., &#38; Ngonga Ngomo, A.-C. (2023). TemporalFC: A Temporal Fact Checking approach over Knowledge Graphs. In T. R. Payne, V. Presutti, G. Qi, M. Poveda-Villalónt, G. Stoilos, L. Hollink, Z. Kaoudi, G. Cheng, &#38; J. Li (Eds.), <i>The Semantic Web – ISWC 2023</i> (Vol. 14265, pp. 465–483). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-031-47240-4_25\">https://doi.org/10.1007/978-3-031-47240-4_25</a>","mla":"Qudus, Umair, et al. “TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs.” <i>The Semantic Web – ISWC 2023</i>, edited by Terry R. Payne et al., vol. 14265, Springer International Publishing, 2023, pp. 465–483, doi:<a href=\"https://doi.org/10.1007/978-3-031-47240-4_25\">10.1007/978-3-031-47240-4_25</a>.","bibtex":"@inproceedings{Qudus_Röder_Kirrane_Ngonga Ngomo_2023, place={Cham}, series={Lecture Notes in Computer Science}, title={TemporalFC: A Temporal Fact Checking approach over Knowledge Graphs}, volume={14265}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-47240-4_25\">10.1007/978-3-031-47240-4_25</a>}, booktitle={The Semantic Web – ISWC 2023}, publisher={Springer International Publishing}, author={Qudus, Umair and Röder, Michael and Kirrane, Sabrina and Ngonga Ngomo, Axel-Cyrille}, editor={R. Payne, Terry and Presutti, Valentina and Qi, Guilin and Poveda-Villalónt, 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} }","short":"U. Qudus, M. Röder, S. Kirrane, A.-C. Ngonga Ngomo, in: T. R. Payne, V. Presutti, G. Qi, M. Poveda-Villalónt, G. Stoilos, L. Hollink, Z. Kaoudi, G. Cheng, J. Li (Eds.), The Semantic Web – ISWC 2023, Springer International Publishing, Cham, 2023, pp. 465–483."},"page":"465–483","intvolume":"     14265","has_accepted_license":"1","main_file_link":[{"open_access":"1","url":"https://papers.dice-research.org/2023/ISWC_TemporalFC/public.pdf"}],"doi":"10.1007/978-3-031-47240-4_25","date_updated":"2025-09-11T09:34:39Z","oa":"1","author":[{"first_name":"Umair","full_name":"Qudus, Umair","id":"83392","last_name":"Qudus","orcid":"0000-0001-6714-8729"},{"first_name":"Michael","id":"67199","full_name":"Röder, Michael","orcid":"https://orcid.org/0000-0002-8609-8277","last_name":"Röder"},{"first_name":"Sabrina","full_name":"Kirrane, Sabrina","last_name":"Kirrane"},{"last_name":"Ngonga Ngomo","id":"65716","full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille"}],"volume":14265,"abstract":[{"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 T EMPORAL FC, 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 T EMPORAL FC\r\non two datasets and compare it to the state of the art in fact-checking and time-point prediction. Our results suggest that T EMPORAL FC outperforms the state of the art on the fact-checking task by 0.13 to 0.15 in terms of Area Under the\r\nReceiver 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.","lang":"eng"}],"file":[{"date_updated":"2025-09-11T09:33:14Z","creator":"uqudus","date_created":"2025-09-11T09:33:14Z","file_size":1938151,"file_name":"temporalfcc.pdf","file_id":"61196","access_level":"closed","content_type":"application/pdf","success":1,"relation":"main_file"}],"publication":"The Semantic Web – ISWC 2023","ddc":["006"],"keyword":["knowgraphs enexa sail nebulaproject dice ngonga saleem roeder qudus"],"language":[{"iso":"eng"}],"year":"2023","quality_controlled":"1","title":"TemporalFC: A Temporal Fact Checking approach over Knowledge Graphs","publisher":"Springer International Publishing","date_created":"2024-01-23T11:38:26Z"},{"doi":"10.1007/978-3-031-19433-7_27","conference":{"start_date":"2022-10-23","name":"International Semantic Web Conference (ISWC)","location":"Hanghzou, China","end_date":"2022-10-27"},"author":[{"id":"83392","full_name":"Qudus, Umair","last_name":"Qudus","orcid":"0000-0001-6714-8729","first_name":"Umair"},{"full_name":"Röder, Michael","id":"67199","orcid":"https://orcid.org/0000-0002-8609-8277","last_name":"Röder","first_name":"Michael"},{"first_name":"Muhammad","full_name":"Saleem, Muhammad","last_name":"Saleem"},{"first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille","id":"65716","last_name":"Ngonga Ngomo"}],"date_updated":"2025-09-11T09:37:16Z","citation":{"mla":"Qudus, Umair, et al. “HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs.” <i>The Semantic Web -- ISWC 2022</i>, edited by Ulrike Sattler et al., Springer International Publishing, pp. 462--480, doi:<a href=\"https://doi.org/10.1007/978-3-031-19433-7_27\">10.1007/978-3-031-19433-7_27</a>.","bibtex":"@inproceedings{Qudus_Röder_Saleem_Ngonga Ngomo, place={Cham}, title={HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-19433-7_27\">10.1007/978-3-031-19433-7_27</a>}, booktitle={The Semantic Web -- ISWC 2022}, publisher={Springer International Publishing}, author={Qudus, Umair and Röder, Michael and Saleem, Muhammad and Ngonga Ngomo, Axel-Cyrille}, editor={Sattler, Ulrike and Hogan, Aidan and Keet, Maria and Presutti, Valentina}, pages={462--480} }","short":"U. Qudus, M. Röder, M. Saleem, A.-C. Ngonga Ngomo, in: U. Sattler, A. Hogan, M. Keet, V. Presutti (Eds.), The Semantic Web -- ISWC 2022, Springer International Publishing, Cham, n.d., pp. 462--480.","apa":"Qudus, U., Röder, M., Saleem, M., &#38; Ngonga Ngomo, A.-C. (n.d.). HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs. In U. Sattler, A. Hogan, M. Keet, &#38; V. Presutti (Eds.), <i>The Semantic Web -- ISWC 2022</i> (pp. 462--480). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-031-19433-7_27\">https://doi.org/10.1007/978-3-031-19433-7_27</a>","ama":"Qudus U, Röder M, Saleem M, Ngonga Ngomo A-C. HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs. In: Sattler U, Hogan A, Keet M, Presutti V, eds. <i>The Semantic Web -- ISWC 2022</i>. Springer International Publishing; :462--480. doi:<a href=\"https://doi.org/10.1007/978-3-031-19433-7_27\">10.1007/978-3-031-19433-7_27</a>","ieee":"U. Qudus, M. Röder, M. Saleem, and A.-C. Ngonga Ngomo, “HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs,” in <i>The Semantic Web -- ISWC 2022</i>, Hanghzou, China, pp. 462--480, doi: <a href=\"https://doi.org/10.1007/978-3-031-19433-7_27\">10.1007/978-3-031-19433-7_27</a>.","chicago":"Qudus, Umair, Michael Röder, Muhammad Saleem, and Axel-Cyrille Ngonga Ngomo. “HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs.” In <i>The Semantic Web -- ISWC 2022</i>, edited by Ulrike Sattler, Aidan Hogan, Maria Keet, and Valentina Presutti, 462--480. Cham: Springer International Publishing, n.d. <a href=\"https://doi.org/10.1007/978-3-031-19433-7_27\">https://doi.org/10.1007/978-3-031-19433-7_27</a>."},"page":"462--480","place":"Cham","publication_status":"accepted","has_accepted_license":"1","publication_identifier":{"isbn":["978-3-031-19433-7"]},"file_date_updated":"2022-12-22T15:45:29Z","user_id":"83392","department":[{"_id":"34"}],"project":[{"_id":"410","name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale"}],"_id":"32509","status":"public","editor":[{"first_name":"Ulrike","last_name":"Sattler","full_name":"Sattler, Ulrike"},{"first_name":"Aidan","full_name":"Hogan, Aidan","last_name":"Hogan"},{"first_name":"Maria","full_name":"Keet, Maria","last_name":"Keet"},{"first_name":"Valentina","full_name":"Presutti, Valentina","last_name":"Presutti"}],"popular_science":"1","type":"conference","title":"HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs","date_created":"2022-08-02T11:56:03Z","publisher":"Springer International Publishing","year":"2022","quality_controlled":"1","language":[{"iso":"eng"}],"ddc":["000"],"keyword":["fact checking · ensemble learning · knowledge graph veracit"],"file":[{"relation":"main_file","success":1,"content_type":"application/pdf","file_name":"hybrid_fact_check_iswc2022.pdf","file_id":"34853","access_level":"closed","file_size":296218,"creator":"uqudus","date_created":"2022-12-22T15:45:29Z","date_updated":"2022-12-22T15:45:29Z"}],"abstract":[{"lang":"eng","text":" We consider fact-checking approaches that aim to predict the veracity of assertions in knowledge graphs. Five main categories of fact-checking approaches for knowledge graphs have been proposed in the recent literature, of\r\nwhich each is subject to partially overlapping limitations. In particular, current text-based approaches are limited by manual feature engineering. Path-based and rule-based approaches are limited by their exclusive use of knowledge graphs as background knowledge, and embedding-based approaches suffer from low accuracy scores on current fact-checking tasks. We propose a hybrid approach—dubbed HybridFC—that exploits the diversity of existing categories of fact-checking approaches within an ensemble learning setting to achieve a significantly better prediction performance. In particular, our approach outperforms the state of the art by 0.14 to 0.27 in terms of Area Under the Receiver Operating Characteristic curve on the FactBench dataset. Our code is open-source and can be found at https://github.com/dice-group/HybridFC."}],"publication":"The Semantic Web -- ISWC 2022"},{"publisher":"ISO Press","date_created":"2021-10-01T06:52:52Z","title":"An Empirical Evaluation of Cost-based Federated SPARQL Query Processing Engines","issue":"6","year":"2021","keyword":["SPARQL","benchmarking","cost-based","cost-free","federated","querying"],"ddc":["000"],"language":[{"iso":"eng"}],"publication":"Semantic Web","abstract":[{"text":"Finding a good query plan is key to the optimization of query runtime. This holds in particular for cost-based federation\r\nengines, which make use of cardinality estimations to achieve this goal. A number of studies compare SPARQL federation engines across different performance metrics, including query runtime, result set completeness and correctness, number of sources selected and number of requests sent. Albeit informative, these metrics are generic and unable to quantify and evaluate the accuracy of the cardinality estimators of cost-based federation engines. To thoroughly evaluate cost-based federation engines, the effect of estimated cardinality errors on the overall query runtime performance must be measured. In this paper, we address this challenge by presenting novel evaluation metrics targeted at a fine-grained benchmarking of cost-based federated SPARQL query engines. We evaluate five cost-based federated SPARQL query engines using existing as well as novel evaluation metrics by using LargeRDFBench queries. Our results provide a detailed analysis of the experimental outcomes that reveal novel insights, useful for the development of future cost-based federated SPARQL query processing engines.","lang":"eng"}],"file":[{"success":1,"relation":"main_file","content_type":"application/pdf","file_size":978478,"file_name":"swj2604.pdf","file_id":"50483","access_level":"closed","date_updated":"2024-01-13T11:35:53Z","date_created":"2024-01-13T11:35:53Z","creator":"uqudus"}],"date_updated":"2025-09-11T09:50:14Z","volume":12,"author":[{"id":"83392","full_name":"Qudus, Umair","orcid":"0000-0001-6714-8729","last_name":"Qudus","first_name":"Umair"},{"last_name":"Saleem","full_name":"Saleem, Muhammad","first_name":"Muhammad"},{"last_name":"Ngonga Ngomo","id":"65716","full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille"},{"last_name":"Lee","full_name":"Lee, Young-Koo","first_name":"Young-Koo"}],"doi":"10.3233/SW-200420","has_accepted_license":"1","publication_identifier":{"issn":["2210-4968"]},"publication_status":"accepted","intvolume":"        12","page":"843-868","citation":{"short":"U. Qudus, M. Saleem, A.-C. Ngonga Ngomo, Y.-K. Lee, Semantic Web 12 (n.d.) 843–868.","bibtex":"@article{Qudus_Saleem_Ngonga Ngomo_Lee, title={An Empirical Evaluation of Cost-based Federated SPARQL Query Processing Engines}, volume={12}, DOI={<a href=\"https://doi.org/10.3233/SW-200420\">10.3233/SW-200420</a>}, number={6}, journal={Semantic Web}, publisher={ISO Press}, author={Qudus, Umair and Saleem, Muhammad and Ngonga Ngomo, Axel-Cyrille and Lee, Young-Koo}, pages={843–868} }","mla":"Qudus, Umair, et al. “An Empirical Evaluation of Cost-Based Federated SPARQL Query Processing Engines.” <i>Semantic Web</i>, vol. 12, no. 6, ISO Press, pp. 843–68, doi:<a href=\"https://doi.org/10.3233/SW-200420\">10.3233/SW-200420</a>.","apa":"Qudus, U., Saleem, M., Ngonga Ngomo, A.-C., &#38; Lee, Y.-K. (n.d.). An Empirical Evaluation of Cost-based Federated SPARQL Query Processing Engines. <i>Semantic Web</i>, <i>12</i>(6), 843–868. <a href=\"https://doi.org/10.3233/SW-200420\">https://doi.org/10.3233/SW-200420</a>","ama":"Qudus U, Saleem M, Ngonga Ngomo A-C, Lee Y-K. An Empirical Evaluation of Cost-based Federated SPARQL Query Processing Engines. <i>Semantic Web</i>. 12(6):843-868. doi:<a href=\"https://doi.org/10.3233/SW-200420\">10.3233/SW-200420</a>","chicago":"Qudus, Umair, Muhammad Saleem, Axel-Cyrille Ngonga Ngomo, and Young-Koo Lee. “An Empirical Evaluation of Cost-Based Federated SPARQL Query Processing Engines.” <i>Semantic Web</i> 12, no. 6 (n.d.): 843–68. <a href=\"https://doi.org/10.3233/SW-200420\">https://doi.org/10.3233/SW-200420</a>.","ieee":"U. Qudus, M. Saleem, A.-C. Ngonga Ngomo, and Y.-K. Lee, “An Empirical Evaluation of Cost-based Federated SPARQL Query Processing Engines,” <i>Semantic Web</i>, vol. 12, no. 6, pp. 843–868, doi: <a href=\"https://doi.org/10.3233/SW-200420\">10.3233/SW-200420</a>."},"_id":"25212","project":[{"_id":"410","name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale"}],"department":[{"_id":"574"}],"user_id":"83392","article_type":"original","file_date_updated":"2024-01-13T11:35:53Z","type":"journal_article","status":"public"}]