Literatura científica selecionada sobre o tema "Knowledge graph creation and curation"
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Artigos de revistas sobre o assunto "Knowledge graph creation and curation"
Debruyne, Christophe, Gary Munnelly, Lynn Kilgallon, Declan O’Sullivan e Peter Crooks. "Creating a Knowledge Graph for Ireland’s Lost History: Knowledge Engineering and Curation in the Beyond 2022 Project". Journal on Computing and Cultural Heritage 15, n.º 2 (30 de junho de 2022): 1–25. http://dx.doi.org/10.1145/3474829.
Texto completo da fonteWeikum, Gerhard, Xin Luna Dong, Simon Razniewski e Fabian Suchanek. "Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases". Foundations and Trends® in Databases 10, n.º 2-4 (2021): 108–490. http://dx.doi.org/10.1561/1900000064.
Texto completo da fonteStocker, Markus, Allard Oelen, Mohamad Yaser Jaradeh, Muhammad Haris, Omar Arab Oghli, Golsa Heidari, Hassan Hussein et al. "FAIR scientific information with the Open Research Knowledge Graph". FAIR Connect 1, n.º 1 (11 de janeiro de 2023): 19–21. http://dx.doi.org/10.3233/fc-221513.
Texto completo da fonteSchwartz, David, e Dov Te'eni. "AI for Knowledge Creation, Curation, and Consumption in Context". Journal of the Association for Information Systems 25, n.º 1 (2024): 37–47. http://dx.doi.org/10.17705/1jais.00862.
Texto completo da fonteMalik, Khalid Mahmood, Madan Krishnamurthy, Mazen Alobaidi, Maqbool Hussain, Fakhare Alam e Ghaus Malik. "Automated domain-specific healthcare knowledge graph curation framework: Subarachnoid hemorrhage as phenotype". Expert Systems with Applications 145 (maio de 2020): 113120. http://dx.doi.org/10.1016/j.eswa.2019.113120.
Texto completo da fonteKhan, Arijit. "Knowledge Graphs Querying". ACM SIGMOD Record 52, n.º 2 (10 de agosto de 2023): 18–29. http://dx.doi.org/10.1145/3615952.3615956.
Texto completo da fonteCroset, Samuel, Joachim Rupp e Martin Romacker. "Flexible data integration and curation using a graph-based approach". Bioinformatics 32, n.º 6 (10 de novembro de 2015): 918–25. http://dx.doi.org/10.1093/bioinformatics/btv644.
Texto completo da fonteAbueed, Raed A. I., e Mehmet Aga. "Sustainable Knowledge Creation and Corporate Outcomes: Does Corporate Data Governance Matter?" Sustainability 11, n.º 20 (10 de outubro de 2019): 5575. http://dx.doi.org/10.3390/su11205575.
Texto completo da fonteLuttmer, Janosch, Mostafa Kandel, Dominik Ehring e Arun Nagarajah. "Automatic knowledge graph creation from engineering standards using the example of formulas". Proceedings of the Design Society 4 (maio de 2024): 423–32. http://dx.doi.org/10.1017/pds.2024.45.
Texto completo da fonteQin, Pengda, Xin Wang, Wenhu Chen, Chunyun Zhang, Weiran Xu e William Yang Wang. "Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 05 (3 de abril de 2020): 8673–80. http://dx.doi.org/10.1609/aaai.v34i05.6392.
Texto completo da fonteTeses / dissertações sobre o assunto "Knowledge graph creation and curation"
Ahmadi, Naser. "A framework for the continuous curation of a knowledge base system". Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS320.
Texto completo da fonteEntity-centric knowledge graphs (KGs) are becoming increasingly popular for gathering information about entities. The schemas of KGs are semantically rich, with many different types and predicates to define the entities and their relationships. These KGs contain knowledge that requires understanding of the KG’s structure and patterns to be exploited. Their rich data structure can express entities with semantic types and relationships, oftentimes domain-specific, that must be made explicit and understood to get the most out of the data. Although different applications can benefit from such rich structure, this comes at a price. A significant challenge with KGs is the quality of their data. Without high-quality data, the applications cannot use the KG. However, as a result of the automatic creation and update of KGs, there are a lot of noisy and inconsistent data in them and, because of the large number of triples in a KG, manual validation is impossible. In this thesis, we present different tools that can be utilized in the process of continuous creation and curation of KGs. We first present an approach designed to create a KG in the accounting field by matching entities. We then introduce methods for the continuous curation of KGs. We present an algorithm for conditional rule mining and apply it on large graphs. Next, we describe RuleHub, an extensible corpus of rules for public KGs which provides functionalities for the archival and the retrieval of rules. We also report methods for using logical rules in two different applications: teaching soft rules to pre-trained language models (RuleBert) and explainable fact checking (ExpClaim)
Oshurko, Ievgeniia. "Knowledge representation and curation in hierarchies of graphs". Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEN024.
Texto completo da fonteThe task of automatically extracting insights or building computational models fromknowledge on complex systems greatly relies on the choice of appropriate representation.This work makes an effort towards building a framework suitable for representation offragmented knowledge on complex systems and its semi-automated curation---continuouscollation, integration, annotation and revision.We propose a knowledge representation system based on hierarchies of graphs relatedwith graph homomorphisms. Individual graphs situated in such hierarchies representdistinct fragments of knowledge and the homomorphisms allow relating these fragments.Their graphical structure can be used efficiently to express entities and their relations. Wefocus on the design of mathematical mechanisms, based on algebraic approaches to graphrewriting, for transformation of individual graphs in hierarchies that maintain consistentrelations between them. Such mechanisms provide a transparent audit trail, as well as aninfrastructure for maintaining multiple versions of knowledge.We describe how the developed theory can be used for building schema-aware graphdatabases that provide schema-data co-evolution capabilities. The proposed knowledgerepresentation framework is used to build the KAMI (Knowledge Aggregation and ModelInstantiation) framework for curation of cellular signalling knowledge. The frameworkallows for semi-automated aggregation of individual facts on protein-protein interactionsinto knowledge corpora, reuse of this knowledge for instantiation of signalling models indifferent cellular contexts and generation of executable rule-based models
Livros sobre o assunto "Knowledge graph creation and curation"
de, Moor Aldo, Lex Wilfried e Ganter Bernhard, eds. Conceptual structures for knowledge creation and communication: 11th International Conference on Conceptual Structures, ICCS 2003, Dresden, Germany, July 21-25, 2003 : proceedings. Berlin: Springer, 2003.
Encontre o texto completo da fonteMachine Knowledge: Creation and Curation of Comprehensive Knowledge Bases. Now Publishers, 2021.
Encontre o texto completo da fonte(Editor), Aldo de Moor, Wilfried Lex (Editor) e Bernhard Ganter (Editor), eds. Conceptual Structures for Knowledge Creation and Communication: 11th International Conference on Conceptual Structures, ICCS 2003, Dresden, Germany, July ... (Lecture Notes in Computer Science). Springer, 2003.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Knowledge graph creation and curation"
Georgoudi, Amalia, Nikolaos Stylianou, Ioannis Konstantinidis, Georgios Meditskos, Thanassis Mavropoulos, Stefanos Vrochidis e Nick Bassiliades. "Towards Knowledge Graph Creation from Greek Governmental Documents". In Advances and Trends in Artificial Intelligence. Theory and Applications, 294–99. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36819-6_26.
Texto completo da fonteVinasco-Alvarez, Diego. "Leveraging Standards in Model-Centric Geospatial Knowledge Graph Creation". In The Semantic Web: ESWC 2022 Satellite Events, 224–33. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11609-4_37.
Texto completo da fonteShinde, Shreya, Shubhangi Gaherwar, Avani Sathe, Malvika Menon e Sheetal Barekar. "Creation of Knowledge Graph for Client Complaint Management System". In Data Management, Analytics and Innovation, 31–43. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2934-1_2.
Texto completo da fonteLodhi, Aminah Bilal, Muhammad Abdullah Bilal, Hafiz Syed Muhammad Bilal, Kifayat Ullah Khan, Fahad Ahmed Satti, Shah Khalid e Sungyoung Lee. "PNRG: Knowledge Graph-Driven Methodology for Personalized Nutritional Recommendation Generation". In Digital Health Transformation, Smart Ageing, and Managing Disability, 230–38. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43950-6_20.
Texto completo da fonteJozashoori, Samaneh, David Chaves-Fraga, Enrique Iglesias, Maria-Esther Vidal e Oscar Corcho. "FunMap: Efficient Execution of Functional Mappings for Knowledge Graph Creation". In Lecture Notes in Computer Science, 276–93. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62419-4_16.
Texto completo da fonteDe Donato, Renato, Martina Garofalo, Delfina Malandrino, Maria Angela Pellegrino, Andrea Petta e Vittorio Scarano. "QueDI: From Knowledge Graph Querying to Data Visualization". In Semantic Systems. In the Era of Knowledge Graphs, 70–86. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59833-4_5.
Texto completo da fonteJozashoori, Samaneh, e Maria-Esther Vidal. "MapSDI: A Scaled-Up Semantic Data Integration Framework for Knowledge Graph Creation". In Lecture Notes in Computer Science, 58–75. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33246-4_4.
Texto completo da fonteJozashoori, Samaneh, Tatiana Novikova e Maria-Esther Vidal. "Poster Paper Data Integration for Supporting Biomedical Knowledge Graph Creation at Large-Scale". In Lecture Notes in Computer Science, 91–96. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-06016-9_9.
Texto completo da fonteHasida, Kôiti. "Personal AI to Maximize the Value of Personal Data while Defending Human Rights and Democracy". In Knowledge and Digital Technology, 239–56. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-39101-9_13.
Texto completo da fonteSrivani, M., Abirami Murugappan e T. Mala. "MathKnowTopic: Creation of a Unified Knowledge Graph-Based Topic Modeling from Mathematical Text Books". In Innovations in Computational Intelligence and Computer Vision, 619–33. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2602-2_47.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Knowledge graph creation and curation"
Huaman, Elwin, e Dieter Fensel. "Knowledge Graph Curation: A Practical Framework". In IJCKG'21: The 10th International Joint Conference on Knowledge Graphs. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3502223.3502247.
Texto completo da fonteLakshmi, Vaibhava R., Gerard Deepak, A. Santhanavijayan e S. Radha. "Knowledge Graph Curation from Text Via Ontologies". In 2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS). IEEE, 2022. http://dx.doi.org/10.1109/icaiss55157.2022.10010816.
Texto completo da fonteBerti-Equille, Laure. "ML-Based Knowledge Graph Curation: Current Solutions and Challenges". In WWW '19: The Web Conference. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3308560.3316522.
Texto completo da fonteKalla, Aparna, R. Shailesh, S. Preetha, Snehal Chandra e Sudeepa Roy. "Scientific Knowledge Graph Creation and Analysis". In 2023 IEEE 8th International Conference for Convergence in Technology (I2CT). IEEE, 2023. http://dx.doi.org/10.1109/i2ct57861.2023.10126238.
Texto completo da fonteShinde, Omkar, e Anish Khobragade. "Knowledge Graph creation on Windows malwares and completion using knowledge graph embedding". In 2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N). IEEE, 2022. http://dx.doi.org/10.1109/icac3n56670.2022.10074567.
Texto completo da fonteKhalid, Mutahira, Hasan Ali Khattak, Arsalan Ahmad e Syed Ahmad Chan Bukhari. "Explainable Prediction of Medical Codes through Automated Knowledge Graph Curation Framework". In 2022 19th International Bhurban Conference on Applied Sciences and Technology (IBCAST). IEEE, 2022. http://dx.doi.org/10.1109/ibcast54850.2022.9990551.
Texto completo da fonteAjmani, Leah, Mo Houtti, Jasmine C. Foriest, Michael Ann Devito, Nicholas Vincent e Isaac Johnson. "Epistemic Injustice in Online Communities: Unpacking the Values of Knowledge Creation and Curation within CSCW Applications". In CSCW '23: Computer Supported Cooperative Work and Social Computing. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3584931.3611280.
Texto completo da fonteM, Arun Kumar, Harsha Prada S, Caroline Dorathy Esther J, Sabareshwaran M. T e Kavitha Devi M K. "Semantic Nexus: Knowledge Graph Creation from CrossNER Data using NLP". In 2023 International Conference on Advanced Computing & Communication Technologies (ICACCTech). IEEE, 2023. http://dx.doi.org/10.1109/icacctech61146.2023.00036.
Texto completo da fontePfitzner, Fabian, Alexander Braun e André Borrmann. "Object Detection-Based Knowledge Graph Creation: Enabling Insight into Construction Processes". In ASCE International Conference on Computing in Civil Engineering 2023. Reston, VA: American Society of Civil Engineers, 2024. http://dx.doi.org/10.1061/9780784485224.023.
Texto completo da fonteXia, Liqiao, Pai Zheng, Yongshi Liang, Ge Zheng e Zhengyang Ling. "Secure Co-Creation of Industrial Knowledge Graph: Graph Complement Method with Federated Learning and ChatGPT". In 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE). IEEE, 2023. http://dx.doi.org/10.1109/case56687.2023.10260382.
Texto completo da fonteRelatórios de organizações sobre o assunto "Knowledge graph creation and curation"
Taylor, Karen, Emily Moynihan e Information Technology Laboratory (U S. ). Information Science and Knowledge Management Branch. The Forefront : A Review of ERDC Publications, Spring 2021. Engineer Research and Development Center (U.S.), junho de 2020. http://dx.doi.org/10.21079/11681/40902.
Texto completo da fonteShapovalov, Viktor B., Yevhenii B. Shapovalov, Zhanna I. Bilyk, Artem I. Atamas, Roman A. Tarasenko e Vitaliy V. Tron. Centralized information web-oriented educational environment of Ukraine. [б. в.], setembro de 2019. http://dx.doi.org/10.31812/123456789/3251.
Texto completo da fonte