An Enhanced Indexing And Ranking Technique On The Semantic Web
With the fast growth of the Internet, more and more information is available on the Web. The Semantic Web has many features which cannot be handled by using the traditional search engines. It extracts metadata for each discovered Web documents in RDF or OWL formats, and computes relations between documents. We proposed a hybrid indexing and ranking technique for the Semantic Web which finds relevant documents and computes the similarity among a set of documents. First, it returns with the most related document from the repository of Semantic Web Documents (SWDs) by using a modified version of the ObjectRank technique. Then, it creates a sub-graph for the most related SWDs. Finally, It returns the hubs and authorities of these document by using the HITS algorithm. Our technique increases the quality of the results and decreases the execution time of processing the user\'s query.
Keywords: Indexing, Ranking Semantic Web Documents, Search Engines, Semantic Web
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ABOUT THE AUTHORS
Ahmed Tolba
Ahmed Tolba got his PhD degree in Electrical Engineering from Wuppertal University, Germany, in 1988, on Computer Vision. He is working as a Dean of the Faculty of Computer Studies at Arab Open University in Kuwait. He is also a professor in department of Computer Science, Faculty of Computers and Information, Mansoura University, Egypt. He published more than 100 previewed papers in international journals and conferences. He is interested in Artificial Intelligence, natural language processing, computer vision, and E-learning.
Nabila Eladawi
Nabila Eladawi got her B.Sc. in information systems from faculty of computers and information , Mansoura University, Egypt, in 2002. She is working as a demonstrator in the department of information systems, faculty of computers and information, Mansoura University, Egypt. She is interested in Semantic Web, Search engines, and natural language processing.
Mohammed Elmogy
Mohammed Elmogy got his PhD degree in computer science from Hamburg University, Germany, in 2010, on Robotics. He is working as an assistant professor in information systems department, faculty of computers and information, Mansoura University, Egypt. He is interested in Robotics, Artificial Intelligence, Semantic Web, and Computer Vision.
Ahmed Tolba
Ahmed Tolba got his PhD degree in Electrical Engineering from Wuppertal University, Germany, in 1988, on Computer Vision. He is working as a Dean of the Faculty of Computer Studies at Arab Open University in Kuwait. He is also a professor in department of Computer Science, Faculty of Computers and Information, Mansoura University, Egypt. He published more than 100 previewed papers in international journals and conferences. He is interested in Artificial Intelligence, natural language processing, computer vision, and E-learning.
Nabila Eladawi
Nabila Eladawi got her B.Sc. in information systems from faculty of computers and information , Mansoura University, Egypt, in 2002. She is working as a demonstrator in the department of information systems, faculty of computers and information, Mansoura University, Egypt. She is interested in Semantic Web, Search engines, and natural language processing.
Mohammed Elmogy
Mohammed Elmogy got his PhD degree in computer science from Hamburg University, Germany, in 2010, on Robotics. He is working as an assistant professor in information systems department, faculty of computers and information, Mansoura University, Egypt. He is interested in Robotics, Artificial Intelligence, Semantic Web, and Computer Vision.
