A Semantic Based Framework for the purpose of Big Data Integration

被引：1

作者：

Ostrowski, David ^{[1
]}

Kim, Mira ^{[2
]}

机构：

[1] Ford Motor Co, Dearborn, MI 48121 USA

[2] Univ Calif Irvine, Dcpt EECS, Irvine, CA 92617 USA

来源：

2017 11TH IEEE INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC) | 2017年

关键词：

D O I：

10.1109/ICSC.2017.62

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

One of the most substantial opportunities in Big Data is to integrate disparate data sources across the enterprise. To realize this goal it can he valuable to leverage environments developed for high speed parallel processing as well as toolkits supporting the development and maintenance of semantic information. In support of this approach a proposed framework and methodology is presented to utilize an ontology-based data integration strategy. Our approach supports a rule-based translation to generate new ontology versions within a fast prototyping environment leveraging the Jena API within the context of the Apache Spark environment.

引用

页码：305 / 309

页数：5

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