Semantic Link Networks: Theory, Applications, and Future Trends

Abstract

The Semantic Link Network (SLN) is a loosely coupled semantic data model for managing the network resources. A SLN consists of three components: a set of semantic nodes, a set of semantic links, and a set of reasoning rules. Semantic nodes can be objects of any types. Semantic links reflect the semantic relations among objects. Reasoning rules, which describe the internal relations among semantic links, are used to derive new semantic links hidden behind. SLN is designed to establish semantic relationships among various resources for extending the current hyperlink network to a semantic-rich network. In this paper, we review the researches on semantic link network from its theory and applications. SLN theories such as schema theory, algebra model, etc, provide us important principles and methods for SLN construction, representation and management. Along with the development of SLN theories, a lot of application scenarios such as document processing, image retrieval, component reuse, phishing target discovering, etc, have been explored as well. Furthermore, we discuss the future trends of SLN and it's potential applications in future Internet of Things.