A Review on the Integration of Deep Learning and Service-Oriented Architecture

A Review on the Integration of Deep Learning and Service-Oriented Architecture

Marcelo Fantinato, Sarajane Marques Peres, Eleanna Kafeza, Dickson K. W. Chiu, Patrick C. K. Hung
Copyright: © 2021 |Pages: 25
DOI: 10.4018/JDM.2021070105
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Abstract

In recent years, machine learning has been used for data processing and analysis, providing insights to businesses and policymakers. Deep learning technology is promising to further revolutionize this processing leading to better and more accurate results. Current trends in information and communication technology are accelerating widespread use of web services in supporting a service-oriented architecture (SOA) consisting of services, their compositions, interactions, and management. Deep learning approaches can be applied to support the development of SOA-based solutions, leveraging the vast amount of data on web services currently available. On the other hand, SOA has mechanisms that can support the development of distributed, flexible, and reusable infrastructures for the use of deep learning. This paper presents a literature survey and discusses how SOA can be enabled by as well as facilitate the use of deep learning approaches in different types of environments for different levels of users.
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Background

This section presents an overview of both areas covered in this paper – deep learning and SOA.

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