The World wide Web consists of millions of interconnected web pages that provide information to the user present in any part of the world. The world wide web is expanding and growing in size and the complexity of the web pages. That is why it is necessary to retrieve the best or the web pages that are more relevant in terms of information for the query entered by the user in search engine. In recent years, semantic search for relevant documents on web has been an important topic of research. Many semantic web search engines have been developed like Ontolook, Swoogle, etc that helps in searching meaningful documents presented on semantic web. To relate entities/texts/documents having same meaning, semantic similarity approach is used based on matching of the keywords which are extracted from the documents. In this paper we have a ranking scheme for the semantic web documents by finding the semantic similarity between the documents and the query which is specified by the user.