Ontology based Semantic Search Engine for Cancer

The idea is to analyze the knowledge about the real world and then create a standard upon stabled rules and relation types to translate the human (natural) language in a machine and human readable language. For that it need to classify and organize data such as text, pictures, videos or database entries in a system with logical connections between data representing the knowledge shared by people. The Ontology provides a framework for the development of Semantic Web and Artificial Intelligence. Here Medical Knowledge Engineering is the Key. This paper deals with the Medical Knowledge Base to build an ontological structure. In this paper Medical Knowledge about cancer is been combined with the semantic web search engine. Based on the introduction of ontology theory, the author uses Protege 2000 of Stanford, the construction and maintenance tool of ontology, designed and completed Medical Knowledge based on Ontology and all details about cancer, cancer categories, its cause, symptoms etc. The system also learned from this details and new details from the searching process. The improvement and learning process is achieved by comparing the details with some knowledge organization systems. Knowledge acquisition in semantic web is done by RDF explorer. RDF scheme defines relationship and those relationship make the searching in a different level