File(s) under embargo

Reason: Publisher requirement

70

days

21

hours

until file(s) become available

Leveraging cloud computing for the semantic web: review and trends

journal contribution
posted on 28.01.2020 by Oluwasegun Adedugbe, Elhadj Benkhelifa, Russell Campion, Feras Al-Obeidat, Anoud Bani Hani, Uchitha Jayawickrama
Semantic and cloud computing technologies have become vital elements for developing and deploying solutions across diverse fields in computing. While they are independent of each other, they can be integrated in diverse ways for developing solutions and this has been significantly explored in recent times. With the migration of web-based data and applications to cloud platforms and the evolution of the web itself from a social, web 2.0 to a semantic, web 3.0 comes as the convergence of both technologies. While several concepts and implementations have been provided regarding interactions between the two technologies from existing research, without an explicit classification of the modes of interaction, it can be quite challenging to articulate the interaction modes; hence, building upon them can be a very daunting task. Hence, this research identifies and describes the modes of interaction between them. Furthermore, a “cloud-driven” interaction mode which focuses on fully maximising cloud computing characteristics and benefits for driving the semantic web is described, providing an approach for evolving the semantic web and delivering automated semantic annotation on a large scale to web applications.

Funding

Zayed University (Grant No. RIF)

History

School

  • Business and Economics

Department

  • Business

Published in

Soft Computing

Volume

24

Pages

5999–6014

Publisher

Springer

Version

AM (Accepted Manuscript)

Rights holder

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Publisher statement

This is a post-peer-review, pre-copyedit version of an article published in Soft Computing. The final authenticated version is available online at: https://doi.org/10.1007/s00500-019-04559-2.

Publication date

2019-11-29

Copyright date

2020

ISSN

1432-7643

eISSN

1433-7479

Language

en

Depositor

Dr Uchitha Jayawickrama. Deposit date: 27 January 2020

Exports