International Journal of Advances in Engineering Science and Technology 47 www.sestindia.org/volume-ijaest/ and www.ijaestonline.com ISSN: 2319-1120 ISSN: 2319-1120 /V2N1: 47-53 © IJAEST Web Mining and Analysis on Semantic Web Search Engine B.SANTHOSH KUMAR Department of Computer Science and Engineering C S I College of Engineering, Ketti, The Nilgiris-643215, Tamilnadu, India b.santhoshkumar@gmail.com M.MOHAN Department of Information Technology C S I College of Engineering, Ketti, The Nilgiris-643215, Tamilnadu, India m.mohansan@gmail.com Abstract— The Web search engines plays a critical role in the mining of data from the large number of web information’s in the form of web pages. The existing Semantic web search engines are failed to retrieve the web pages with the desired amount of accuracy. The ranking needs to work on whole of the annotated knowledge database. The proposed system uses the layered architecture which will increase the information retrieval accuracy using relations. But in this relation-based page rank algorithm to be used in conjunction with Semantic web search engine. It emphasize on the information extracted from the user queries on annotated resources. Relevance between queries is measured in terms of probability that a retrieved resource actually contains the relations based on the user query. It tends to produce results in terms of both time complexity and accuracy. Keywords- Semantic Web, Knowledge Retrieval, Search Process I. INTRODUCTION The search engines are comes to play ever a more critical role because of the tremendous growth of information available to end users through the Web. It is always less uncommon that obtained result sets provide a burden of useless pages. The next-generation Web architecture, represented by the Semantic Web, provides the layered architecture possibly allowing overcoming this limitation. Semantic search engines have been proposed, which allow increasing information retrieval accuracy by exploiting a key content of Semantic Web resources that is relations. In order to rank results, most of the existing solutions need to work on the whole annotated knowledge base. The aim of this project is to show how to make use of relations in Semantic Web page annotations with the aim of generating an ordered result set, where pages that best fit the user query are displayed first. To evaluate the feasibility of the proposed approach, first constructed a controlled Semantic Web environment. To do, selected the well-known travel.owl ontology written in the OWL language and modified it by adding new relations in order to make it more suitable for demonstrating system functionality. We then created a knowledge base by either downloading or automatically generating a set of web pages in the field of tourism, and embedded into RDF semantic annotations based on the travel.owl ontology. Finally, designed the remaining modules of the architecture, including a Webpage database, a crawler application, a knowledge database, an OWL parser, a query interface and the true search engine module embedding the proposed into ranking logic. The crawler application collects annotated Web pages from the Semantic Web (in this case, represented by the controlled environment and its Web page collection) including RDF metadata and originating OWL ontology. RDF metadata are interpreted by the OWL parser and stored in the knowledge database. A graphics user interface allows for the definition of a query, which is passed on to the relation-based search logic. The ordered result set generated by this latter module is finally presented to the user. The details of the system workflow will be provided in the following sections, starting with the query definition process, since it was through the analysis of its dynamics that came to the identification of our ranking strategy. The Query