A Cloud Computing Capability Model for Large-Scale Semantic Annotation
Oluwasegun Adedugbe, Elhadj Benkhelifa, Anoud Bani-Hani

TL;DR
This paper proposes a cloud computing capability model to enable large-scale semantic annotation of web content, addressing scalability and integration challenges in semantic technologies.
Contribution
It introduces a novel mapping of semantic annotation requirements to cloud computing mechanisms, forming a comprehensive capability model for web-scale semantic annotation.
Findings
Established a set of requirements for web semantic annotation
Mapped cloud mechanisms to these requirements
Proposed a cloud-based framework for large-scale semantic annotation
Abstract
Semantic technologies are designed to facilitate context-awareness for web content, enabling machines to understand and process them. However, this has been faced with several challenges, such as disparate nature of existing solutions and lack of scalability in proportion to web scale. With a holistic perspective to web content semantic annotation, this paper focuses on leveraging cloud computing for these challenges. To achieve this, a set of requirements towards holistic semantic annotation on the web is defined and mapped with cloud computing mechanisms to facilitate them. Technical specification for the requirements is critically reviewed and examined against each of the cloud computing mechanisms, in relation to their technical functionalities. Hence, a mapping is established if the cloud computing mechanism's functionalities proffer a solution for implementation of a requirement's…
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