Survey on Data Integration Technologies for Relational Data and Knowledge Graph

被引：0
作者：
Gao Y.-J. [1 ]
Ge C.-C. [2 ]
Guo Y.-X. [1 ]
Chen L. [1 ]
机构：
[1] College of Computer Science and Technology, Zhejiang University, Hangzhou
[2] Data Intelligence Innovation Lab, Huawei Cloud Computing Technologies Co. Ltd., Hangzhou
来源：
Ruan Jian Xue Bao/Journal of Software | 2023年 / 34卷 / 05期
关键词：
data integration; knowledge graph (KG); relational data;
D O I：
10.13328/j.cnki.jos.006808
中图分类号：
学科分类号：
摘要：
Recently, big data is considered a critical strategic resource by many countries and regions. However, difficult data circulation and insufficient data regulation commonly exist in the big data era, thereby leading to the serious phenomenon of data silos, poor data quality, and difficulty in unleashing the potential of data elements. This provokes researchers to explore data integration techniques for breaking data barriers, enabling data sharing, improving data quality, and activating the potential of data elements. Relational data and knowledge graphs, as two significant forms of data organization and storage, have been widely applied in real life. To this end, this study focuses on relational data and knowledge graphs to summarize and analyze the key technologies of data integration, including entity resolution, data fusion, and data cleaning. Finally, it prospects future research directions. © 2023 Chinese Academy of Sciences. All rights reserved.
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页码：2365 / 2391
页数：26
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