Dept. of Computer Science and Artificial Intelligence, Faculty of Computer Science and Engineering, Jeddah, Saudi Arabia.
Faculty of Business and Information Technology, University of Ontario Institute of Technology, Oshawa, ON, Canada.
Citation: Farid Bourennani, Mike Bourque, “A Content-Based Schema Matching Tool”, The World of Computer Science and Information Technology Journal (WSCIT). 2019 Volume 9, Issue 5, pp.22.27.
Abstract—Schema matching (SM) is a fundamental task of data integration and data warehousing. Often SM is performed manually which is time consuming and error prone. Furthermore, existing SM tools do not scale well to large schemas. To alleviate these challenges, a novel tool is proposed for automated schema mapping based on the content by matching data entities exclusively based on the content. The resulting topology is convenient to visually explore the relationship among database entities even in large volume. Also, a post-processing algorithm based on data types is proposed for further enhancement clustering results. We present a case study to demonstrate the efficiency and the practicality of the proposed tool.
Keywords-Schema Matching; Schema Mapping; Data Integration; Content-Based Schema Matching; Instance-Based Schema Matching; Visualization.