Connecting Asset Stores with Graph Databases
Metadata
- Publisher
- SMPTE
- Doc Type
- Journal Article
- Content Type
- Original Research
- Abbreviated Title
- SMPTE Motion Imaging Jour.
- Volume
- 133, No. 2, pp. 28–36
- Abstract
- As media organizations accumulate diverse data from various sources, effective data integration and retrieval becomes increasingly critical. Graph databases offer a flexible and efficient platform for integration by leveraging graph-based data models and querying mechanisms. Graph databases can seamlessly integrate disparate data sets regardless of their original format or structure. Knowledge can be added to the graph through the application of semantic meaning to the data. Machine learning (ML) algorithms can extract additional information from data to enhance knowledge graphs (KGs). This paper demonstrates how knowledge graphs offer unique capabilities for understanding patterns over collections of large data sets.
- Publication Date
- 2024-04-01
- DOI
10.5594/JMI.2024/XBZC2345- ISSN
- Print:
1545-0279| Electronic:2160-2492 - Link
- https://doi.org/10.5594/JMI.2024/XBZC2345
- Author(s)
- Roger SacilottoShailendra MathurRob Gonsalves
- Keyword(s)
- Knowledge Graphs, Data Integration, Semantic Understanding, Machine Learning
- Copyright
- © 2024 SMPTE
Bibliographic Reference(s)
- Worldwide Web Consortium (W3C). The Semantic Web Made Easy [Online]. Available: https://www.w3.org/RDF/Metalog/docs/sw-easy. EXTERNAL
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- Worldwide Web Consortium (W3C) RDF Primer [Online]. Available: https://www.w3.org/TR/rdf-primer/. EXTERNAL
- About MovieLabs: Mission [Online]. Available: https://movielabs.com/about/movielabs-mission/. EXTERNAL
- Aidan Hogan, “Knowledge Graphs,” ACM Computing Surveys 54 (4): pp. 1–37, Jul. 2021. EXTERNAL
- Worldwide Web Consortuim (W3C) RDF 1.2 Concepts and Abstract Syntax, Section 1: Graph-based Data Model [Online]. Available: https://www.w3.org/TR/32-concepts/#data-model. EXTERNAL
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- Worldwide Web Consortium (W3C) Media Types Issues for Text RDF Formats [Online]. Available: https://www.w3.org/2008/01/rdf-media-types. EXTERNAL
- Worlwide Web Consortium (W3C) Resource Description Framework (RDF) Schema Specification 1.0 [Online]. Available: https://www.w3.org/2001/sw/RDFCore/Schema/20010913/. EXTERNAL
- Worldwide Web Consortium (W3C) SKOS Simple Knowledge Organization System [Online]. Available: https://www.w3.org/TR/2009/REC-skos-reference-20090818/. EXTERNAL
- Worlwide Web Consortuim (W3C) Web Ontology Language (OWL) [Online]. Available: https://www.w3.org/OWL/. EXTERNAL
- Renzo Angles, “Survey of Graph Database Models,” ACM Computing Surveys 40 (1) pp. 1:1–39, Feb. 2008. EXTERNAL
- Worldwide Web Consortium (W3C) SPARQL 1.1 Query Language [Online]. Available: https://www.w3.org/TR/151-query/. EXTERNAL
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- Apache TinkerPop™ [Online]. Available: https://tinkerpop.apache.org/gremlin.html. EXTERNAL
- Yiheng Liu, “Summary of CHATGPT/gpt-4 research and perspective towards the future of large language models,” arXiv preprint arXiv:2304.01852. May 2023. EXTERNAL
- Anis Koubaa. “GPT-4 vs. GPT-3.5: A concise showdown.” Apr. 2023. EXTERNAL
- Alec Radford, “Learning Transferable Visual Models from Natural Language Supervision,” in Proc. Intern. Conf. on Mach. Learning (PMLR), Feb. 2021. EXTERNAL
- S. Pan, “Unifying Large Language Models and Knowledge Graphs: A Roadmap,” arXiv preprint arXiv:2306.08302. June 2023. EXTERNAL
- Yuqi Zhu, “LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities.” arXiv preprint arXiv:2305.13168, May 2023. EXTERNAL
- Wang, Xiting, “Multi-level Recommendation Reasoning over Knowledge Graphs with Reinforcement Learning.” in Proc. of the ACM Web Conf. 2022, pp. 2098–2018, Apr. 2022. EXTERNAL
- Wang, Xiaolong, Yufei Ye, and Abhinav Gupta. “Zero-shot Recognition via Semantic Embeddings and Knowledge Graphs.” in Proc. of the IEEE Conf. on Comp. Vis. and Pattern Recognition. Mar. 2018. EXTERNAL
- IETF RFC 3987 [Active*]
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Roger Sacilotto, Shailendra Mathur, and Rob Gonsalves; Connecting Asset Stores with Graph Databases, MIJ 2024, Volume 133, Number 2 (pp. 28 to 36); SMPTE, 2024. Available at https://doi.org/10.5594/JMI.2024/XBZC2345
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Roger Sacilotto, Shailendra Mathur, and Rob Gonsalves; Connecting Asset Stores with Graph Databases, MIJ 2024, Volume 133, Number 2 (pp. 28 to 36); SMPTE, 2024. Available at https://doi.org/10.5594/JMI.2024/XBZC2345
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Roger Sacilotto, Shailendra Mathur, and Rob Gonsalves; Connecting Asset Stores with Graph Databases, MIJ 2024, Volume 133, Number 2 (pp. 28 to 36); SMPTE, 2024. Available at https://doi.org/10.5594/JMI.2024/XBZC2345
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<span class="citation">Roger Sacilotto, Shailendra Mathur, and Rob Gonsalves; <cite>Connecting Asset Stores with Graph Databases</cite>, MIJ 2024, Volume 133, Number 2 (pp. 28 to 36); SMPTE, 2024. Available at <a href="https://doi.org/10.5594/JMI.2024/XBZC2345" target="_blank" rel="noopener">https://doi.org/10.5594/JMI.2024/XBZC2345</a></span>
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Roger Sacilotto, Shailendra Mathur, and Rob Gonsalves; Connecting Asset Stores with Graph Databases, MIJ 2024, Volume 133, Number 2 (pp. 28 to 36); SMPTE, 2024
doi: 10.5594/JMI.2024/XBZC2345
url: https://doi.org/10.5594/JMI.2024/XBZC2345
doi: 10.5594/JMI.2024/XBZC2345
url: https://doi.org/10.5594/JMI.2024/XBZC2345
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<li> Roger Sacilotto, Shailendra Mathur, and Rob Gonsalves; <cite id="bib-10-5594-jmi-2024-xbzc2345">Connecting Asset Stores with Graph Databases</cite>, MIJ 2024, Volume 133, Number 2 (pp. 28 to 36); SMPTE, 2024 <span class="doi">10.5594/JMI.2024/XBZC2345</span> </li>