Enhancing the relevance of Semantic Web information retrieval results using extension theory

Traditional Web Service search methodology dependant on keywords is time consuming and inefficient. The search results are often inexact. The substantive reason is that, the description of Web Service lacks semantic information. Search Engines can't accomplish the communication automatically and intelligently between the services. At the same time, the Semantic Web depends strongly on the schematic ontologies that organize underlying data for the use of comprehensive machine understanding. Hence, the success of the Semantic Web depends heavily on the development of ontologies, which necessitates fast and simple engineering of ontologies and prevention of a knowledge acquisition bottleneck. This paper discourses the issue of prevailing semantic conflicts in Web mining and explains how intelligent agents with the help of ontology can eliminate some kinds of these semantic conflicts as a result of which relevance of retrieved results is improved. The paper proposes to use the different extension methods that can rule out different kinds of semantic conflicts effectively.