Research Of Semantic Search Engine Of Blasting Industry

With the rapid development of the Internet, the information-sharing mode of thetraditional Internet has been cannot satisfy the search needs of various users, it’s become moreand more difficult to find out the information what the users really want exactly, especially inthe face of increasing amounts of data. Meanwhile, the demand for information sharing andprocessing between sectors, locations, companies, etc, has become more urgent. SemanticWeb technology to solve this problem caused widespread concern in all areas of society.Semantic Web technology now has the technical foundation for the promotion to theprofessional field. If Semantic Web technology can be brought into the blasting areas, willgreatly promote the development of the information construction of the blast industry.Nowadays, there are information shared problem between provinces and amount of dataproblem. In order to bring Semantic Web technology to the blasting industry, Not only shouldwe research theory and applications of the Semantic Web, but also develop a suitableSemantic Web framework, which can reduce the cost of the evolution from relational data tosemantic data.In the research of the Semantic Web technologies, our laboratory has made asemi-automatic Construction of blasting the domain ontology tool to solve the problem ofbuilding a blasting industry of ontology, and the Blasting digital archives, as the center of theblasting industry of information storage.For the information storage condition of Blasting industry, we propose a solution ofinformation storage and query based on Oracle11G, which can reduces the difficulty ofblasting areas of the original mass data migration.In addition, this paper raises the overall framework of the semantic network constructionin the blasting industry, and the framework of the semantic search engine, use RDFa markupto achieve the unity of the original provinces model to facilitate semantic search crawling, andbuild a unified information model, making the center of the search engine to ignore theprovincial database internal details. Greatly improving the precision search in massiveamounts of data.At last, make a summary of progress and future work related to this topic.