The state-of-the-art in web-scale semantic information processing for cloud computing

TL;DR

This paper reviews current semantic information processing techniques in cloud computing, highlighting challenges and proposing future research directions for distributed semantic reasoning and parallel semantic computing.

Contribution

It provides an overview of existing semantic processing technologies in cloud computing and suggests new research avenues for distributed and parallel semantic reasoning.

Findings

Semantic processing helps resolve ambiguity and overload in cloud data.

Existing technologies are effective but face scalability challenges.

Future research should focus on distributed and parallel semantic reasoning.

Abstract

Based on integrated infrastructure of resource sharing and computing in distributed environment, cloud computing involves the provision of dynamically scalable and provides virtualized resources as services over the Internet. These applications also bring a large scale heterogeneous and distributed information which pose a great challenge in terms of the semantic ambiguity. It is critical for application services in cloud computing environment to provide users intelligent service and precise information. Semantic information processing can help users deal with semantic ambiguity and information overload efficiently through appropriate semantic models and semantic information processing technology. The semantic information processing have been successfully employed in many fields such as the knowledge representation, natural language understanding, intelligent web search, etc. The purpose of this report is to give an overview of existing technologies for semantic information processing in cloud computing environment, to propose a research direction for addressing distributed semantic reasoning and parallel semantic computing by exploiting semantic information newly available in cloud computing environment.