Schema matching is considered as one of the essential phases of data integration in database systems. The main aim of the schema matching process is to identify the correlation between schema which helps later in the data integration process. The main issue concern of schema matching is how to support the merging decision by providing the correspondence between attributes through syntactic and semantic heterogeneous in data sources. There have been a lot of attempts in the literature toward utilizing database instances to detect the correspondence between attributes during schema matching process. Many approaches based on instances have been proposed aiming at improving the accuracy of the matching process. This paper set out a classification of schema matching research in database system exploiting database schema and instances. We survey and analyze the schema matching techniques applied in the literature by highlighting the strengths and the weaknesses of each technique. A deliberate discussion has been reported highlights on challenges and the current research trends of schema matching in database. We conclude this paper with some future work directions that help researchers to explore and investigate current issues and challenges related to schema matching in contemporary databases. Keywords-Data integration; instance-based schema matching; schema matching; semantic matching; syntactic matching INTRODUCTION I.
CITATION STYLE
A., A., Nordin, A., Alzeber, M., & Zaid, A. (2017). A Survey of Schema Matching Research using Database Schemas and Instances. International Journal of Advanced Computer Science and Applications, 8(10). https://doi.org/10.14569/ijacsa.2017.081014
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