Cited by 262Semantic Web and OntologiesAdvanced Graph Neural NetworksData Quality and Management

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?

Fensel, Dieter, Şimşek, Umutcan, Angele, Kevin, Huaman, Elwin, Kärle, Elias, Panasiuk, Oleksandra, Toma, Ioan, Umbrich, Jürgen, Wahler, Alexander·2020·Knowledge Graphs

DOI 10.1007/978-3-030-37439-6_1

Open this paper in CoChat — free account

Integrity signals

Registry

Crossref · 10.1007/978-3-030-37439-6_1

Cites

54 of 54 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

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
The knowledge level
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

Show all 55 references

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)

Items 101–200 of 262

Material feeding and scheduling method for smart discrete manufacturing workshops based on a temporal knowledge graph and dual neural networks
Jing, W., Lin, X., Niu, X., Liu, J., Zhang, Y., Hu, Y., & Chen, Y. (2025) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2025.2544558 · Cited by 4
DeScan: Censorship-resistant indexing and search for Web3
de Vos, M., Ishmaev, G., & Pouwelse, J. A. (2023) · Future Generation Computer Systems · doi:10.1016/j.future.2023.11.008 · Cited by 4
The New Version of the Corpus Data Management System “Tugan Tel” Using Graph Knowledge Base
Mukhamedshin, D., Gatiatullin, A. R., & Абрекович, Г. Р. (2024) · IEEE International Conference on Problems of Informatics, Electronics and Radio Engineering (PIERE) · doi:10.1109/piere62470.2024.10804932 · Cited by 4
A Deep Learning Architecture Based on Advanced Textual Language Models for Detecting Disease Through Its Symptoms Associated with a Reinforcement Learning Algorithm
Ellouze, M., & Belguith, L. H. (2023) · Communications in computer and information science · doi:10.1007/978-3-031-37231-5_10 · Cited by 4
Review of Knowledge Graph and Its Vertical Applications in Industry
Li, J., Feng, Z., Zhang, M., Jing, F., & Guo, Q. (2023) · Chinese Control Conference (CCC) · doi:10.23919/ccc58697.2023.10240572 · Cited by 4
Approach Based on Bayesian Network and Ontology for Identifying Factors Impacting the States of People with Psychological Problems from Data on Social Media
Ellouze, M., & Belguith, L. H. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-49333-1_10 · Cited by 4
DDE KG Editor: A data service system for knowledge graph construction in geoscience
Hou, C., Liu, K., Wang, T., Shi, S., Yan, L., Zhu, Y., Hu, X., Wang, C., Zhou, C., & Lv, H. (2024) · Geoscience Data Journal · doi:10.1002/gdj3.245 · Cited by 4
Automatic FAQ Generation Using Text-to-Text Transformer Model
Vasisht, S., Tirthani, V., Eppa, A., Koujalgi, P., & Srinath, R. (2022) · International Conference for Emerging Technology (INCET) · doi:10.1109/incet54531.2022.9823967 · Cited by 4
Heron, a Knowledge Graph editor for intuitive implementation of Python-based experimental pipelinesPreprint
Dimitriadis, G., Svahn, E., MacAskill, A. F., & Akrami, A. (2024) · eLife · doi:10.7554/elife.91915 · Cited by 4
LUMEN: Enhancing IoT System Observability with Multi-Agent Large Language Models and Knowledge Graphs
Nedisan Videsjorden, A., Song, H., Goknil, A., Roman, D., & Soylu, A. (2026) · ACM Transactions on Internet of Things · doi:10.1145/3772077 · Cited by 5
Entities recommendations using contextual information
Saidi, I., Mahammed, N., Klouche, B., & Bencherif, K. (2024) · International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering · doi:10.11591/ijece.v14i4.pp4336-4342 · Cited by 3
Retrieving and discovering new knowledge from documents' abstracts in scientific databases: Proposing a query-based abstractive summarization model
Dashtaki, N. A., CheshmehSohrabi, M., Pashootanizadeh, M., & Kashani, H. B. (2025) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2025.100366 · Cited by 3
Continuous Data-driven Personas Generation: An LLM-based Knowledge Graph Approach
Sugiyama, R., Washizaki, H., Ubayashi, N., Tanahashi, R., Hirabayashi, M., Okuda, S., & Toriumi, K. (2025) · IEEE International Requirements Engineering Conference (RE) · doi:10.1109/re63999.2025.00067 · Cited by 3
A systematic literature review on knowledge mapping for project risk management in the construction industry
Ullah, S., Deng, X., Amaechi, C. V., Anbar, D. R., & Ashraf, M. W. (2026) · Frontiers in Built Environment · doi:10.3389/fbuil.2025.1677904 · Cited by 3
Leveraging Semantic Technologies for Collaborative Inference of Threatening IoT Dependencies
Guittoum, A., Aïssaoui, F., Bolle, S., Boyer, F., & Palma, N. D. (2023) · ACM SIGAPP Applied Computing Review · doi:10.1145/3626307.3626310 · Cited by 3
Neuro-symbolic approach for querying BIM models
Stéphane, R., Anthony, D., & Roxin, A. (2023) · International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) · doi:10.1109/sitis61268.2023.00019 · Cited by 3
A User-Driven Hybrid Neuro-Symbolic Approach for Knowledge Graph Creation from Relational Data
Stütz, J.-D., Karras, O., Oelen, A., & Auer, S. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-81375-7_10 · Cited by 3
A knowledge graph-based approach for recognizing older adults’ behavior in urban parks
Zhang, K. J., Cao, K., & Li, W. (2025) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2025.2499084 · Cited by 3
Research on the Construction and Practice of Intelligent Courses from the Perspective of Knowledge Graph: A Case Study of English Lexicology
Cao, H. (2025) · Education and Social Work · doi:10.63313/esw.9066 · Cited by 3
Update the power project knowledge graph of power project using Neo4j Graph Database
Liu, H., Cao, Y., Liu, P., Yang, H., Sun, R., Huang, Y., Gui, Y., & Li, W. (2021) · International Conference of Social Computing and Digital Economy (ICSCDE) · doi:10.1109/icscde54196.2021.00082 · Cited by 3
SENSIBLE: SEquestered aNd SynergIstic BLockchain Ecosystem
Kshirsagar, M., Vaidya, G., Yao, Y., Kasar, S. L., & Ryan, C. (2022) · Engineering Reports · doi:10.1002/eng2.12586 · Cited by 3
Research Directions in Process Modeling and Mining Using Knowledge Graphs and Machine Learning
Miller, J. A., & Mahmud, R. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-23515-3_7 · Cited by 3
Contrastive Semantic Similarity Learning for Multi-Hop Question Answering over Event-Centric Knowledge Graphs
Tang, W., Kong, Q., Mao, W., & Wu, X. (2022) · IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS) · doi:10.1109/ccis57298.2022.10016335 · Cited by 3
ASRC:A Knowledge Graph Relation Construction Model based on Active Learning and Semantic Recognition
Sun, L., Hu, W., Xu, K., Chen, Y., Sun, Q., & Wang, J. (2022) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata55660.2022.10020502 · Cited by 3
A System of Data Assets Registration and Catalog Management
Li, X., & Xia, X. (2023) · IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB) · doi:10.1109/bmsb58369.2023.10211143 · Cited by 3
Multi-aspect attentive text representations for simple question answering over knowledge base
Zeng, Z., Li, Y., Yong, J., Tao, X., & Liu, V. (2023) · Natural Language Processing Journal · doi:10.1016/j.nlp.2023.100035 · Cited by 3
TON-ViT: A Neuro-Symbolic AI Based on Task Oriented Network with a Vision Transformer
Zhuo, Y., Jiang, N., Kirkpatrick, A. W., Couperus, K. S., Tran, O., Beck, J., DeVane, D., Candelore, R., McKee, J. L., Gorbatkin, C., et al. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-48593-0_12 · Cited by 3
Research on Double-Graphs Knowledge-Enhanced Intelligent Diagnosis
Song, Y., Dai, D., Zhang, K., Zan, H., Hu, B., Wu, P., & Zhu, C. (2024) · Communications in computer and information science · doi:10.1007/978-981-99-9864-7_21 · Cited by 3
A Case Study on Multi-Countries Money Laundering Scheme and A Proposed Automatic Detection System
Tan, X., Tse, T.-F. T., Yiu, S., & Lam, H.-M. H. (2024) · International Conference on Cyber Warfare and Security · doi:10.34190/iccws.19.1.1984 · Cited by 3
Evaluating School Location Based on a Territorial Spatial Planning Knowledge Graph
Xu, X., Hao, J., & Shen, J. (2024) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi13060173 · Cited by 3
Cryptanalysis of the SIMON Cypher Using Neo4j
Cook, J., Rehman, S. U., & Khan, M. A. (2024) · International Conference on Electrical, Computer and Energy Technologies (ICECET) · doi:10.1109/icecet61485.2024.10698687 · Cited by 3
Ontology in Dance Domain—A Survey
Paul, S., Das, P. P., & Rao, K. S. (2024) · Journal on Computing and Cultural Heritage · doi:10.1145/3690767 · Cited by 3
Advancing Capability Matching in Manufacturing Reconfiguration with Large Language Models
Mo, F., Chaplin, J. C., SANDERSON, D. R., & Ratchev, S. M. (2024) · Lecture notes in mechanical engineering · doi:10.1007/978-3-031-74485-3_24 · Cited by 3
Efficient and Tractable Conflict Detection in Knowledge Graphs via Path Analysis
Wang, Y., Song, Q., Zheng, L., & Li, X. (2025) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2025.3575948 · Cited by 3
PCI Workplace: A decentralized collaboration framework for AI based problem-solving
Suh, Y., Woo, S., Eom, B., Park, D.-H., Lim, S., & Park, C. (2021) · International Conference on Information and Communication Technology Convergence (ICTC) · doi:10.1109/ictc52510.2021.9620799 · Cited by 3
SERAG: Semantic Entity Retrieval from Arabic knowledge Graphs
Esmeir, S. (2021) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.4560652 · Cited by 3
Building Trust in Conversational AI: A Comprehensive Review and Solution Architecture for Explainable, Privacy-Aware Systems using LLMs and Knowledge GraphPreprint
Zafar, A., Parthasarathy, V. B., Van, C. L., Shahid, S., Khan, A. I., & Shahid, A. (2023) · doi:10.36227/techrxiv.24009351 · Cited by 3
Research on the Prospect of Knowledge Graph Completion Based on the Federated Setting
Zhao, A., Liu, Y., Wei, S., Yu, L., Feng, W., & Gu, Z. (2023) · IEEE International Conference on Data Science in Cyberspace · doi:10.1109/dsc59305.2023.00019 · Cited by 2
Big Data Approaches to Identifying Crisis Misinformation
Xue, H., & Shen, C. (2024) · Wiley eBooks · doi:10.1002/9781394184972.ch13 · Cited by 2
Automated Attack Knowledge Graph Construction with Large Language Models
Wang, Z., Fei, S., Hu, Y., Shan, D., Xiao, S., You, L., & Chen, P. (2025) · International Conference on Computer and Multimedia Technology (ICCMT) · doi:10.1145/3757749.3757864 · Cited by 2
An LLM-based QA system for Chinese Painting and Calligraphy with Knowledge Graphs and external documents
Wan, J., Li, X., Zhang, H., Zou, A., & Wang, R. (2025) · npj Heritage Science · doi:10.1038/s40494-025-02219-3 · Cited by 2
Automatic Similarity Feature Combination for Knowledge Graph Alignment via Adaptive-Designed Particle Swarm Optimization With Genetic Programming
Xue, X., Waqas, S. M., Liu, W., & Lin, J. C. (2026) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2026.3683654 · Cited by 2
A Study on Knowledge Embedding Method for Extending Contextual Information of Words
Kim, Y., & Gim, J. (2022) · The Journal of Korean Institute of Information Technology · doi:10.14801/jkiit.2022.20.11.29 · Cited by 2
Synchronous Condenser-Based Intelligent Question Answering System Based on Knowledge Graph
Zhang, D., Yao, Y., Li, J., Zhang, G., Li, Y., Xu, C., & Wu, Q. (2023) · Smart innovation, systems and technologies · doi:10.1007/978-981-19-7184-6_43 · Cited by 2
A KG-Based Integrated UAV Approach for Engineering Semantic Trajectories in the Cultural Heritage Documentation Domain
Kotis, K., Angelis, S., Moraitou, E., Kopsachilis, V., Papadopoulou, E.-E., Soulakellis, N. A., & Vaitis, M. (2023) · Remote Sensing · doi:10.3390/rs15030821 · Cited by 2
Review: A Roadmap to Use Nonstructured Data to Discover Multitarget Cancer Therapies
Scoarta, S., Küçükosmanoğlu, A., Bindt, F., Pouwer, M. G., & Westerman, B. A. (2023) · JCO Clinical Cancer Informatics · doi:10.1200/cci.22.00096 · Cited by 2
Efficient decision-making in SMEs: leveraging knowledge graphs with Neo4j and AI vision
Mo, F., Rehman, H. U., Elshafei, B., Chaplin, J. C., SANDERSON, D. R., Martínez-Arellano, G., & Ratchev, S. M. (2023) · IET conference proceedings. · doi:10.1049/icp.2023.1736 · Cited by 2
A novel joint extraction model based on cross-attention mechanism and global pointer using context shield window
Zhai, Z., Fan, R., Huang, J., Xiong, N. N., Zhang, L., Wan, J., & Zhang, L. (2024) · Computer Speech & Language · doi:10.1016/j.csl.2024.101643 · Cited by 2
Enterprise violation risk deduction combining generative AI and event evolution graph
Zhong, C., Li, P., Wang, J., Xiong, X., Lv, Z., Zhou, X., & Zhao, Q. (2024) · Expert Systems · doi:10.1111/exsy.13622 · Cited by 2
ELLAS Architecture and Process: Collecting and Curating Data on Women’s Presence in STEM
Berardi, R. C. G., Auceli, P. H. S., Maciel, C. D. O., Fritoli, R., Dávila, G. A., Guzman, I. R., & Mendes, L. B. (2024) · Journal on Interactive Systems · doi:10.5753/jis.2024.3853 · Cited by 2
Smart recommender for the configuration of software project development teams
Rodríguez‐García, M. Á., García‐Sánchez, F., & Valencia‐García, R. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.125141 · Cited by 2
Towards a Generic Knowledge Graph Construction Framework for Privacy Awareness
Karalka, C., Μεδίτσκος, Γ., Παπουτσόγλου, Μ., & Bassiliades, N. (2024) · IEEE International Conference on Cyber Security and Resilience (CSR) · doi:10.1109/csr61664.2024.10679399 · Cited by 2
Research on the Optimization of English Translation Teaching Mode in Colleges and Universities Driven by Knowledge Mapping
Zhao, Y., & Yan, Y. (2024) · Applied Mathematics and Nonlinear Sciences · doi:10.2478/amns-2024-2897 · Cited by 2
Teaching Reform and Exploration of Python Programming Course Based on Knowledge Graph
Liang, J. (2025) · Journal of Educational Research and Policies · doi:10.53469/jerp.2025.07(01).06 · Cited by 2
From Data to Decisions: Enterprise-Level Domain-Specific Graph Retrieval-Augmented Generation Systems for Advanced Question Answering
Varma, S., Shivam, S., Natarajan, S., Banerjee, A., & Roy, S. (2025) · IEEE International Conference on Big Data and Smart Computing (BigComp) · doi:10.1109/bigcomp64353.2025.00016 · Cited by 2
Semantic Graph Queries on Linked Data in Knowledge Graphs
Dörpinghaus, J., & Stefan, A. (2021) · Studies in computational intelligence · doi:10.1007/978-3-030-82397-9_4 · Cited by 2
A Lifecycle Framework for Semantic Web Machine Learning Systems
Breit, A., Waltersdorfer, L., Ekaputra, F. J., Miksa, T., & Sabou, M. (2022) · Communications in computer and information science · doi:10.1007/978-3-031-14343-4_33 · Cited by 2
Construction Method of City-Level Geographic Knowledge Graph Based on Geographic Entity
Liu, J., Guo, D., Liu, G., Yanli, Z., Yang, W., & Tang, L. (2022) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-3-031-08017-3_12 · Cited by 2
SG-RC: SG-CIM Grid Knowledge Graph Relationship Complementation Model Based on Entropy Uncertainty and Semantic Recognition
Zhang, P., Gao, S., Shen, Y., Yang, S., & Sun, L. (2023) · IEEE International Conference on Big Data Security on Cloud, IEEE International Conference on High Performance and Smart Computing, and IEEE International Conference on Intelligent Data and Security (BigDataSecurity/HPSC/IDS) · doi:10.1109/bigdatasecurity-hpsc-ids58521.2023.00040 · Cited by 2
Visualization analysis of research hotspots and frontier development of knowledge graph constructionPreprint
Wang, Z., Wang, L., & Wang, G. (2022) · Research Square · doi:10.21203/rs.3.rs-2180206/v1 · Cited by 2
Operationalising Human Security in the Contemporary Operating Environment: Proposing Population Intelligence (POPINT)
Anning, S., Fenton, T., Muraszkiewicz, J., & Watson, H. (2022) · The Journal of Intelligence Conflict and Warfare · doi:10.21810/jicw.v4i3.3802 · Cited by 1
Simultaneous Extraction of Entities and Relations Based on Pre-trained Language Model and Pre-defined Language Templates
Shang, C., Qin, B., Peng, P., & Wang, H. (2022) · IEEE International Conference on e-Business Engineering (ICEBE) · doi:10.1109/icebe55470.2022.00046 · Cited by 1
Evaluating the Effectiveness of Graph and Timeline-Based Visualizations for Search Engine Results: A Comparative Study
Qureshi, S., & Haring, K. S. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-48044-7_12 · Cited by 1
Exploring Production System Knowledge Graph Applications Using a Simulation Framework
Birtic, M., Senington, R., & Syberfeldt, A. (2024) · Advances in transdisciplinary engineering · doi:10.3233/atde240171 · Cited by 1
Smart Healthy Age-Friendly Environments (SHAFE) Bridging Innovation to Health Promotion and Health Service Provision
Luca, V. D., Marston, H. R., Angelini, L., Militeva, N., Klimczuk, A., Fabian, C., Papitto, P., Bernardo, J., Ventura, F. I. Q. S., da Silva, R. C. G., et al. (2024) · IntechOpen eBooks · doi:10.5772/intechopen.1004109 · Cited by 1
Supporting the working life exposome: Annotating occupational exposure for enhanced literature search
Thompson, P., Ananiadou, S., Basinas, I., Brinchmann, B. C., Cramer, C., Galea, K. S., Ge, C., Georgiadis, P., Kirkeleit, J., Kuijpers, E., et al. (2024) · PLoS ONE · doi:10.1371/journal.pone.0307844 · Cited by 1
A Ontology Construction Method of Course Knowledge Graph Based on Dependency of Knowledge Points
Bin, Q., Zuhairi, M. F., Morcos, J. J., & Lu, Z. (2025) · International Conference on Ubiquitous Information Management and Communication (IMCOM) · doi:10.1109/imcom64595.2025.10857583 · Cited by 1
Application and research progress of artificial intelligence in shale gas exploration and development
Zhu, X., Hong-ming, J., Huang, Y., & Han, Y. (2025) · Unconventional Resources · doi:10.1016/j.uncres.2025.100300 · Cited by 1
Beyond IoT: AGI as a Transformative Solution for the Internet of Everything and Relationship Explosion
Mao, W., Lin, Y., Xu, J., Mao, L., Ding, J., Ning, H., & Daneshmand, M. (2025) · IEEE Internet of Things Journal · doi:10.1109/jiot.2025.3649804 · Cited by 1
A Method for Constructing a Knowledge Graph of Safety Standards for Energetic Materials Based on Large Language Models
Liu, Y. C., Lan, J., Fu, Q., Wu, Y., Chu, Q., & Shi, X. (2025) · International Conference on Artificial Intelligence, Virtual Reality and Visualization (AIVRV) · doi:10.1109/aivrv67401.2025.11350873 · Cited by 1
NICE-Food KG: A knowledge graph for the analysis of the Nutritional, Ingredient, Contaminant, and Environmental characteristics of food for food system research
Bindt, F., Ocké, M. C., de Jonge, R., Toxopeus, I. B., & Fensel, A. (2026) · Future Foods · doi:10.1016/j.fufo.2026.100935 · Cited by 1
Architectures of knowing: toward a theory of AI-augmented observability in enterprise knowledge systems
Toumi, A., Wamba, S. F., & Hafsi, M. (2026) · Journal of Knowledge Management · doi:10.1108/jkm-09-2025-1360 · Cited by 1
Finding Similar Entities Across Knowledge Graphs
Aghaei, S., & Fensel, A. (2021) · doi:10.5121/csit.2021.110301 · Cited by 1
Getting Formal Ontologies Closer to Final Users Through Knowledge Graph Visualization: Interpretation and Misinterpretation
Pileggi, S. F. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-08760-8_50 · Cited by 1
Heron, a Knowledge Graph editor for intuitive implementation of Python-based experimental pipelines
Dimitriadis, G., Svahn, E., MacAskill, A. F., & Akrami, A. (2025) · eLife · doi:10.7554/elife.91915.3 · Cited by 1
MultAtt-RippleNet: Multi-attribute and Knowledge-based Attention Fusion Recommendation Model
Chen, H., & Li, Q.-G. (2023) · Journal of Physics Conference Series · doi:10.1088/1742-6596/2644/1/012006 · Cited by 1
MKGS: Maintains the Original Structure of Knowledge Graph
Zheng, Y., Cen, J., Sun, S., Yin, D., Li, J., & Wang, Y. (2023) · IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) · doi:10.1109/wi-iat59888.2023.00074 · Cited by 1
Cybersecurity Knowledge Graph Enables Targeted Data Collection for Cybersecurity Analysis
Ma, C., Zhang, D., Zhang, J., Wang, L., Li, H., & Gu, Z. (2023) · IEEE International Conference on Data Science in Cyberspace · doi:10.1109/dsc59305.2023.00091 · Cited by 1
Design Issues in Implementation of Decentralized AI-data commons Framework
Suh, Y., Woo, S., Eom, B., Park, D.-H., Lim, S., & Park, C. (2023) · International Conference on Information and Communication Technology Convergence (ICTC) · doi:10.1109/ictc58733.2023.10392898 · Cited by 1
Towards the Analysis of Longitudinal Data in Knowledge Graphs on Job Ads
Dörpinghaus, J., Weil, V., & Binnewitt, J. (2024) · Studies in computational intelligence · doi:10.1007/978-3-031-57320-0_4 · Cited by 1
Impact of Clinical Features on Disease Diagnosis Using Knowledge Graph Embedding and Machine Learning: A Detailed Analysis
Dhiman, S., Thukral, A., & Bedi, P. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-64070-4_21 · Cited by 1
Open Manufacturing Capability Network Supported by Formal Ontologies
Ameri, F., Shenoy, M., Hasanzadeh, A., & Kapoor, S. (2024) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-71637-9_21 · Cited by 1
Knowledge graph completion for scholarly knowledge graph
Taufiqurrahman, T., Wiharja, K. R. S., & Wulandari, G. S. (2024) · Bulletin of Social Informatics Theory and Application · doi:10.31763/businta.v8i2.657 · Cited by 1
Research Landscape of Sustainable Development of Digital Talents in the Era of Digital Economy
Ren, L., Wu, J., & Wang, Y. (2025) · Journal of Educational Research and Policies · doi:10.53469/jerp.2025.07(03).26 · Cited by 1
Focused digital cohort selection from social media using the metric backbone of biomedical knowledge graphs
Guo, Z., Felag, J., Rozum, J. C., Correia, R. B., Wang, X., & Rocha, L. M. (2025) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2025.104847 · Cited by 1
IntelliMedChain: Knowledge Driven and Blockchain Powered Data Sharing Framework for Smart HealthcarePreprint
Kshirsagar, M., Vaidya, G., Yao, Y., Kasar, S. L., & Ryan, C. (2022) · doi:10.22541/au.165226321.19441546/v1 · Cited by 1
Research on multimodal link prediction method based on Vision Transformer and convolutional neural networkPreprint
Liu, Y., Ren, Z., Liu, X., Wang, X., Wang, Y., & Wang, H. (2024) · Research Square · doi:10.21203/rs.3.rs-4489200/v1 · Cited by 1
A Framework for Knowledgebase Curation using Cognitive Web Architecture
Mattam, X. J., & Lourdusamy, R. (2021) · International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) · doi:10.1109/icccis51004.2021.9397152
iKNOW: A platform for knowledge graph construction for biodiversity
Babalou, S., Costa, D. S., Bruelheide, H., Kattge, J., Römermann, C., Wirth, C., & König‐Ries, B. (2022) · Biodiversity Information Science and Standards · doi:10.3897/biss.6.93867
Knowledge Graphs for COVID-19: A Survey
Minoli, M., & Ambegoda, T. D. (2012) · Internet of things · doi:10.1007/978-3-031-28631-5_1
Significance of knowledge graph in SMART learning
Nithya, S., & Apinayaprethi, K. N. (2023) · International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA) · doi:10.1109/icaeca56562.2023.10200739
Neuro-Logic Learning for Relation Reasoning over Event Knowledge Graph
Tang, W., Kong, Q., Luo, Y., & Mao, W. (2023) · IEEE International Conference on Intelligence and Security Informatics (ISI) · doi:10.1109/isi58743.2023.10297212
News Text Sentiment Classification Method Based on Knowledge Graph
Xu, Y., Ji, T., & Li, Z. (2023) · International Conference on Public Management, Digital Economy and Internet Technology (ICPDI) · doi:10.4108/eai.1-9-2023.2338760
Multi-dimensional Knowledge Graph Embedding with Entity Type Information
Park, J.-H., & Gim, J. (2023) · The Journal of Korean Institute of Information Technology · doi:10.14801/jkiit.2023.21.11.63
Schema Based Knowledge Graph for Clinical Knowledge Representation from Structured and Un-structured Oncology Data
Tariq, F., Khan, S. A., & Fraz, M. M. (2023) · Lecture notes in electrical engineering · doi:10.1007/978-981-16-6775-6_43
Semantic Exploring and Analysis on Visualization of Research Articles Based on Knowledge Graphs
Yadav, N., & Gopinathan, D. (2023) · International Conference on Informatics (ICI) · doi:10.1109/ici60088.2023.10421022
Knowledge Graph for Multi Hazard Risk Assessment and Management in Rainfall Prone Regions
Senarathne, R., Withanage, W. D. U. I., Dilshani, M. G. S. U., Sandarangi, R. M. N., Samarasekara, P., & Abeygunawardhana, P. K. W. (2023) · International Conference on Advancements in Computing (ICAC) · doi:10.1109/icac60630.2023.10417606
Content Relation Reconstruction and Mining for Knowledge Graphs
杜, 亚. (2024) · Interdisciplinary Science Letters · doi:10.12677/isl.2024.81006
Knowledge Graph Collaborative Large Language Model for Computer Components RecommendationPreprint
Wang, Y., Chen, S., & Jin, K. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4862890
Semantic Similarity Definition
Couto, F. M., Lamúrias, A., & Ruas, P. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-95502-7.00085-3

Authors: Fensel, D., Şimşek, U., Angele, K., Huaman, E., Kärle, E., Panasiuk, O., Toma, I., Umbrich, J., & Wahler, A.
Affiliations: Universität Innsbruck (AT)
ORCID: Fensel, Dieter
Angele, Kevin
Huaman, Elwin
Kärle, Elias
Panasiuk, Oleksandra
Toma, Ioan
Venue: Knowledge Graphs
Publisher: Springer International Publishing
Published: 2020
Pages: 1-10
DOI: 10.1007/978-3-030-37439-6_1
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 ›

Are you an author, or do you see a problem with this page? Request a review

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.

Introduction: What Is a Knowledge Graph?

Overview

Integrity signals

Verification

Claims the paper makes

Citations

Cites

Cited by

Related

Metadata

Record

About these checks

Data sources