Semantic Web Technologies and Artificial Neural Networks for Intelligent Web Knowledge Source Discovery

Abstract

This chapter is focused on presenting new and recent techniques, suchas the combination of agent-based technologies and Arti cial Neural Network (ANN)models that can be used for intelligent web knowledge source discovery in the newand emergent Semantic Web.The purpose of the Semantic Web is to introduce semantic content in the hugeamount of unstructured or semi-structured information sources available on the webby using ontologies. An ontology provides a vocabulary about concepts and theirrelationships within a domain, the activities taking place in that domain, and thetheories and elementary principles governing that domain. The lack of an integratedview of all sources and the existence of heterogeneous domain ontologies, drives newchallenges in the discovery of knowledge sources relevant to a user request. Neweffcient techniques and approaches for developing web intelligence are presented inthis chapter, to help users avoid irrelevant web search results and wrong decisionmaking.In summary, the contributions of this chapter are twofold:- the benefits of combining Arti cial Neural Networks with SemanticWebTechnologies are discussed, and- an Artificial Neural Network-based intelligent agent with capabilities fordiscovering distributed knowledge sources is presented.