{"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} }","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>.","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>.","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>","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."},"project":[{"name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale","grant_number":"860801","_id":"410"}],"ddc":["000"],"department":[{"_id":"34"}],"publication":"The Semantic Web -- ISWC 2022","publisher":"Springer International Publishing","date_created":"2022-08-02T11:56:03Z","doi":"10.1007/978-3-031-19433-7_27","file":[{"success":1,"creator":"uqudus","file_size":296218,"content_type":"application/pdf","relation":"main_file","date_updated":"2022-12-22T15:45:29Z","file_id":"34853","file_name":"hybrid_fact_check_iswc2022.pdf","access_level":"closed","date_created":"2022-12-22T15:45:29Z"}],"type":"conference","year":"2022","place":"Cham","date_updated":"2024-01-13T11:40:36Z","language":[{"iso":"eng"}],"has_accepted_license":"1","author":[{"last_name":"Qudus","id":"83392","first_name":"Umair","full_name":"Qudus, Umair"},{"full_name":"Röder, Michael","first_name":"Michael","last_name":"Röder"},{"full_name":"Saleem, Muhammad","first_name":"Muhammad","last_name":"Saleem"},{"full_name":"Ngonga Ngomo, Axel-Cyrille","last_name":"Ngonga Ngomo","id":"65716","first_name":"Axel-Cyrille"}],"title":"HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs","file_date_updated":"2022-12-22T15:45:29Z","user_id":"83392","conference":{"name":"International Semantic Web Conference (ISWC)","start_date":"2022-10-23","location":"Hanghzou, China","end_date":"2022-10-27"},"keyword":["fact checking · ensemble learning · knowledge graph veracit"],"editor":[{"full_name":"Sattler, Ulrike","first_name":"Ulrike","last_name":"Sattler"},{"first_name":"Aidan","last_name":"Hogan","full_name":"Hogan, Aidan"},{"full_name":"Keet, Maria","first_name":"Maria","last_name":"Keet"},{"full_name":"Presutti, Valentina","last_name":"Presutti","first_name":"Valentina"}],"_id":"32509","abstract":[{"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.","lang":"eng"}],"status":"public","page":"462--480","publication_identifier":{"isbn":["978-3-031-19433-7"]},"publication_status":"accepted","jel":["D"]}