Extracting and Reducing the Semantic Information Content of Web Documents to Support Semantic Document Retrieval

Ranking and optimization of web service compositions represent challenging areas of research with significant implication for realization of the "Web of Services" vision. The semantic web, where the semantics information is indicated using machine-process able language such as the Web Ontology Language (OWL) "Semantic web service" use formal semantic description of web service functionality and enable automated reasoning over web service compositions. These semantic web services can then be automatically discovered, composed into more complex services, and executed. Automating web service composition through the use of semantic technologies calculating the semantic similarities between outputs and inputs of connected constituent services, and aggregate these values into a measure of semantics quality for the composition. It propose a novel and extensible model balancing the new dimensions of semantic quality ( as a functional quality metric) with QoS metric, and using them together as a ranking and optimization criteria. It also demonstrates the utility of Genetic Algorithms to allow optimization within the context of a large number of services foreseen by the "Web of Service" vision. To reduce the semantics of the web documents then to support semantic document retrieval by using Network Ontology Language (NOL) and to improve QoS as a ranking and optimization.