Applications of Nature-Inspired Algorithms in Different Aspects of Semantic Web

Abstract

Nature has always inspired us all the waggle dance of Honey bee, the school of whales and the swarm of ants, each element when observed carefully has the abundance of teachings. If we carefully observe nature, we find that although Nature seems to be very simple and systematic, it hides many complexities underneath it. As technology also follows the same principle of ‘simple-yet-complex’, the researchers have always tried to apply the learning from Nature to complex technological Algorithms used to solve few real life human problems. Since the past decade, there has been a rapid increase of research in this field. Today Nature Inspired algorithms have permeated into almost all areas of sciences. Although it had been applied to various areas of sciences, the scope of this paper is limited to its application in the domain of The Semantic Web. The main objective of Semantic web applications is to obtain, manage and utilize the huge amount of information that is available in either structured semistructured or unstructured databases in distributed environment. This is an emerging domain and is advancing towards more and more intelligent and human oriented applications. This paper presents a survey of vital nature-Inspired techniques that can be used for optimizing various areas of Semantic web applications such as knowledge base, content filtering, Information Retrieval and Inference mechanism.