Connecting Asset Stores with Graph Databases

被引:0
|
作者
Sacilotto R. [1 ]
Mathur S. [1 ]
Gonsalves R. [1 ]
机构
[1] Avid, United States
来源
SMPTE Motion Imaging Journal | 2024年 / 133卷 / 02期
关键词
DATA INTEGRATION; KNOWLEDGE GRAPHS; MACHINE LEARNING; SEMANTIC UNDERSTANDING;
D O I
10.5594/JMI.2024/XBZC2345
中图分类号
学科分类号
摘要
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. © 2002 Society of Motion Picture and Television Engineers, Inc.
引用
收藏
页码:28 / 36
页数:8
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