The DOI matches its Crossref record; 54 of the 55 references it cites were found in a registry or an index.
Introduction: What Is a Knowledge Graph?
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Cites
A relational model of data for large shared data banks
Codd, E. F. (1970) · Communications of the ACM · doi:10.1145/362384.362685 · Cited by 5,547
Freebase: a collaboratively created graph database for structuring human knowledge
Bollacker, K., Evans, C., Paritosh, P., Sturge, T., & Taylor, J. (2008) · Proceedings of the 2008 ACM SIGMOD international conference on Management of data · doi:10.1145/1376616.1376746 · Cited by 4,852
A relational model of data for large shared data banks
Codd, E. F. (1983) · Communications of the ACM · doi:10.1145/357980.358007 · Cited by 4,796
Wikidata: a free collaborative knowledgebase
Vrandečić, D., & Krötzsch, M. (2014) · Communications of the ACM · doi:10.1145/2629489 · Cited by 3,342
DBpedia – A large-scale, multilingual knowledge base extracted from Wikipedia
Lehmann, J., Isele, R., Jakob, M., Jentzsch, A., Kontokostas, D., Mendes, P. N., Hellmann, S., Morsey, M., van Kleef, P., Auer, S., et al. (2015) · Semantic Web · doi:10.3233/sw-140134 · Cited by 3,168
Newell, A. (1982) · Artificial Intelligence · doi:10.1016/0004-3702(82)90012-1 · Cited by 2,589
Yago: a core of semantic knowledge
Suchanek, F. M., Kasneci, G., & Weikum, G. (2007) · Proceedings of the 16th international conference on World Wide Web · doi:10.1145/1242572.1242667 · Cited by 2,512
DBpedia: A Nucleus for a Web of Open Data
Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., & Ives, Z. (2007) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-76298-0_52 · Cited by 2,454
Toward an architecture for never-ending language learning
Carlson, A., Betteridge, J., Kisiel, B., Settles, B., Hruschka, E., & Mitchell, T. (2010) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v24i1.7519 · Cited by 2,000
CYC: a large-scale investment in knowledge infrastructure
Lenat, D. B. (1995) · Communications of the ACM · doi:10.1145/219717.219745 · Cited by 1,969
Research works printed but not linked: 7
- D. Fensel, M. Erdmann, R. Studer, Ontology groups: semantically enriched subnets of the WWW, in Proceedings of the 1st International Workshop Intelligent Information Integration During the 21st German Annual Conference on Artificial Intelligence, Freiburg, Germany, September 1997
- I.J. Goodfellow, Y. Bengio, A.C. Courville, Deep Learning. Adaptive Computation and Machine Learning (MIT Press, Cambridge, 2016)
- G.W.F. Hegel, Science of Logic, vol. I, Section 3, Chapter 1, A. The Specific Quantum (Translated by A.V. Miller). Atlantic Highlands: Humanities Paperback Library, Originally appeared (1812)
- F. Mahdisoltani, J. Biega, F.M. Suchanek, YAGO3: a knowledge base from multilingual Wikipedias, in Proceedings of Seventh Biennial Conference on Innovative Data Systems Research (CIDR2015), Online Proceedings, Asilomar, CA, 4–7 January 2015. www.cidrdb.org
- J. Z. Pan, G. Vetere, J. M. Gómez-Pérez, H. Wu (eds.), Exploiting Linked Data and Knowledge Graphs in Large Organisations (Springer, Cham, 2017b)
- G. Qi, J. Tang, J. Du, J.Z. Pan, Y. Yu (eds.), Linked Data and Knowledge Graph—7th Chinese Semantic Web Symposium and 2nd Chinese Web Science Conference (CSWS2013): Revised Selected Papers, Shanghai, China, 12–16 August 2013. Springer CCIS, vol. 406
- G. Qi, H. Chen, K. Liu, H. Wang, Q. Ji, T. Wu, Knowledge Graph (Springer, Cham, 2020)
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Functional Knowledge Graph Towards Knowledge Application and Data Management for General Users
Hu, X. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-7235-3_19
Yang, Y., Wang, J., Hui, Z., & Gao, S. (2024) · International Conference on Artificial Intelligence and Electromechanical Automation (AIEA) · doi:10.1109/aiea62095.2024.10692440
Semantic Enrichment of Textual Data Through Knowledge Extraction
Devi, D. R. N., Kasu, H., Line, M., Roshni, N., & Shreya, P. (2024) · Lecture notes in electrical engineering · doi:10.1007/978-981-97-8043-3_171
Natural Language Processing for Earth resource management: a case of H2 Golden Retriever research
Olabanjo, O. A., Seurin, P., Wiggins, J., Pratt, L., Rana, L., Yasaei, R., & Renard, G. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-23595-5.00009-7
Liu, X., Wang, Z., & Wang, F. (2024) · IEEE Access · doi:10.1109/access.2024.3518614
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Dörpinghaus, J., Weil, V., Rockenfeller, R., & Mangroliya, M. P. (2024) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2024.101183
Knowledge Graphs: Representation and Reasoning
Bhuyan, B. P., Ramdane-Chérif, A., Singh, T. P., & Tomar, R. (2024) · Studies in computational intelligence · doi:10.1007/978-981-97-8171-3_6
Graph techniques for enhancing knowledge graph integration: A comprehensive study and applications
Bharambe, U., Kurte, K. R., & Durbha, S. S. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-29654-3.00008-9
Family relationship prediction based on the knowledge graph
Wang, Y., Tong, J., Yang, Y., Zhao, Y., Wang, W., Dong, X., Pang, Y., Fan, W., & Xing, Z. (2024) · International Conference on Signal Processing and Communication Technology (SPCT) · doi:10.1145/3712464.3712489
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Gupta, R., Sharma, S. J., Punjabi, M., & Gupta, S. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-30040-0.00017-5
Aligning Food Ingredients with Multiple Semantic Resources
Sasanski, D., Todorovski, A., Trpeski, B., Trajanov, D., Eftimov, T., & Stojanov, R. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-86162-8_2
Next Word Prediction Using Knowledge Graph
Alshiya, S., & Usha, K. (2025) · International Conference on Machine Learning and Autonomous Systems (ICMLAS) · doi:10.1109/icmlas64557.2025.10967741
Wang, W. (2025) · Research Publications (Maastricht University) · doi:10.26481/dis.20250522ww
Yu, H., Cao, H., Cui, Y., & Dong, C. (2025) · The Journal of Supercomputing · doi:10.1007/s11227-025-07467-5
Distributed Incremental Ontology Reasoning over Dynamic T-boxes
de Lima, B. R. C. A., Kramer, M., & Pinheiro, V. H. C. (2024) · Artificial Intelligence and Cloud Computing Conference (AICCC) · doi:10.1145/3719384.3719446
Dimitriadis, G., Svahn, E., MacAskill, A. F., & Akrami, A. (2025) · eLife · doi:10.7554/elife.91915.3.sa2
Using natural language definitions and language models for relationship classification
Amorim, M. M., Lopes, A., Rodrigues, F. H., & Carbonera, J. L. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.114154
SurgiGard: Surgical Instrument Handover Graph-Based Supervision and Robust Detection
Katsarou, K., Mouakher, A., Chojecki, P., Przewozny, D., Runde, D., & Bosse, S. (2025) · IEEE International Conference on Healthcare Informatics (ICHI) · doi:10.1109/ichi64645.2025.00059
Wang, M., Liu, J., Wu, P., Xiao, L.-N., & Yusong (2025) · Chinese Control and Decision Conference (CCDC) · doi:10.1109/ccdc65474.2025.11090303
Chained Prediction Algorithm for Multi-Spatial Knowledge Graphs
Wang, M., Wu, P., Xiao, L.-N., Yusong, & Liu, J.-W. (2025) · Chinese Control and Decision Conference (CCDC) · doi:10.1109/ccdc65474.2025.11090937
Gao, F., Zhang, L., Zhang, B., Wang, W., Liu, W., Zhang, J., Liu, H., Qiu, S., Huang, K., & Zhang, M. (2025) · International Conference on Machine Learning and Neural Networks · doi:10.1145/3747227.3747237
Towards a Dynamic Knowledge Graph for Academic Orientation: A Comparative Study of Update Approaches
Elkaimbillah, Z., Mcharfi, Z., Khoual, M., & Asri, B. E. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-032-01536-5_44
Deng, Y., Hou, S., & Zhang, M. (2025) · IEEE Access · doi:10.1109/access.2025.3624142
HRAN-MKR:Multi-task Recommendation based on Heterogeneous Relation Attention Network
Chen, P., Ma, J., Sabhae, M. A. A., Abduljabbar, Z. A., & Nyangaresi, V. O. (2025) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn64981.2025.11228364
Verma, G., Rebholz-Schuhmann, D., & Madden, M. G. (2024) · Figshare · doi:10.6084/m9.figshare.26678090
Bougioukas, K. I. (2024) · Octopus · doi:10.57874/e7mr-3m04
Youn, J. S. (2024) · eScholarship (California Digital Library)
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A Strategic Community Roadmap for an Australian FAIR Vocabulary Ecosystem
Wong, M., Atkins, N., Boyle, D., Dharmawardena, K., Hobern, D., McEachern, S., & Wyborn, L. (2025) · ANU Open Research (Australian National University) · doi:10.25911/n6k8-f540
KG-PTP: A Knowledge Graph-Driven Approach for Pedestrian Trajectory Prediction
Cao, X., Pang, C., Liu, H., Lyu, L., Li, W., & Duan, J. (2025) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2025.3619843
Hamdani, Y., & Türkarslan, E. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-13109-6_12
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Qi, B., Xiao, X., & Liang, J. (2026) · Springer proceedings in physics · doi:10.1007/978-981-95-3449-4_30
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Wang, W., Zhu, A., Hu, T., Wang, S., & Dai, Y. (2026) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2026.3674228
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Bruyat, J. (2024) · theses.fr (ABES) · doi:10.70675/ca58b31fz8354z4fe8z8e41z6faed4f3b88a
Pham, L. Y. C., Le, D. M., Hoang, M. K., Nguyen, D. D. A., & Ta, Q. T. (2025) · International Conference on Electrical, Computer and Energy Technologies (ICECET) · doi:10.1109/icecet63943.2025.11471982
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Zhao, F., Yi, Y., Lu, D., Ma, J., & Zhang, N. (2025) · IEEE International Conference on Applied Mathematics, Modeling and Computer Simulation (AMMCS) · doi:10.1109/ammcs65761.2025.11459850
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Lei, W. (2025) · World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM) · doi:10.1109/wcmeim67790.2025.11466598
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Wu, X., Yan, S., & Zhipeng, X. (2026) · International Conference on Artificial Intelligence and Advanced Autonomous Systems · doi:10.1145/3813723.3813738
Deveci, A., Erkan, M., Medeni, İ. T., Medeni, T. D., Uzkafali, A., & Özkan, A. (2026) · Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering · doi:10.33769/aupse.1907258
multari, M., Carrière, M., Amoros-Gabarron, X., Kumar, K., Debnath, P., Damy, A., Andrianirina, L., Lobentanzer, S., Sáez-Rodríguez, J., Jaubert‐Possamai, S., et al. (2026) · New Phytologist · doi:10.1111/nph.71382
Grounding large language models in an anthropological knowledge graph: A neuro-symbolic approach
Artz, M. (2026) · Human Organization · doi:10.1080/00187259.2026.2674887
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Maoliniyazi, A., Ma, C., & Meng, X. (2026) · International Conference on Computer Supported Cooperative Work in Design (CSCWD) · doi:10.1109/cscwd68734.2026.11581529
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Souza, P. V. D. C., & Rosenfeld, L. (2026) · IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) · doi:10.1109/fuzz69877.2026.11626437
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Zawad, N., & Khan, L. R. (2026) · Communications in computer and information science · doi:10.1007/978-981-92-1546-1_40
Li, M., Ruijie, T., & Li, Y. (2026) · Earth Science-Journal of China University of Geosciences · doi:10.3799/dqkx.2026.210
Sarakatsianou, D., & Koloniari, G. (2025) · Proceedings of the International Conference on Cultural Heritage and New Technologies
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Chekuri, S., & Fox, E. A. (2026) · ACM/IEEE Joint Conference on Digital Libraries · doi:10.1145/3805696.3846035
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Pereira, C. Y. S., Araújo, G. S., Silva, M. S., dos Santos, S. M., Rêgo, R. C. D. S., & Lobato, F. M. F. (2026) · Anais do Symposium on Knowledge Discovery, Mining and Learning (KDMiLe) · doi:10.5753/kdmile.2026.31792
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Beniwal, H., & Färber, M. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-42029-9_28
Metadata
- Authors
- Fensel, D., Şimşek, U., Angele, K., Huaman, E., Kärle, E., Panasiuk, O., Toma, I., Umbrich, J., & Wahler, A.
- Affiliations
- Universität Innsbruck (AT)
- Venue
- Knowledge Graphs
- Publisher
- Springer International Publishing
- Published
- 2020
- Pages
- 1-10
- OpenAlex
- W3004035003
- Cited by
- 244
- References
- 55
- Citations by year
- 2026: 20 · 2025: 53 · 2024: 73 · 2023: 52 · 2022: 27 · 2021: 15 · 2020: 3
- FWCI
- 39.26
- Type
- book chapter
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Springer eBooks (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Graph Neural Networks
- Physical Sciences › Computer Science › Information Systems › Data Quality and Management
- Keywords
- knowledge graphs, data integration, conceptual definitions, Google Knowledge Graph
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.