Semantic web technologies and artificial neural networks for intelligent web knowledge source discovery

Abstract

This chapter is focused on presenting new and recent techniques, such as the combination of agent-based technologies and Artificial Neural Network (ANN) models that can be used for intelligent web knowledge source discovery in the new and emergent Semantic Web. The purpose of the Semantic Web is to introduce semantic content in the huge amount of unstructured or semi-structured information sources available on the web by using ontologies. An ontology provides a vocabulary about concepts and their relationships within a domain, the activities taking place in that domain, and the theories and elementary principles governing that domain. The lack of an integrated view of all sources and the existence of heterogeneous domain ontologies, drives new challenges in the discovery of knowledge sources relevant to a user request. New efficient techniques and approaches for developing web intelligence are presented in this chapter, to help users avoid irrelevant web search results and wrong decision making. In summary, the contributions of this chapter are twofold: 1. The benefits of combining Artificial Neural Networks with Semantic Web Technologies are discussed. 2 An Artificial Neural Network-based intelligent agent with capabilities for discovering distributed knowledge sources is presented.