Hyeonsook Kim

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Model Driven Data Integration is a data integration approach that proactively incorporates and utilizes metadata across the data integration process. By decoupling data and metadata, MDDI drastically reduces complexity of data integration; whilst also providing an integrated standard development method, which is associated with Model Driven Architecture.(More)
Data mining combines machine learning, statistics and visualization techniques to discover and extract knowledge. One of the biggest challenges that higher education faces is to improve student retention (National Audition Office, 2007). Student retention has become an indication of academic performance and enrolment management. Our project uses data mining(More)
Over the decades, Enterprise Architecture (EA) has been researched to supply all the necessary components for enterprise system modelling including taxonomies, meta-models, architecture development methods, and modelling tools. The main benefits of EA are the knowledge infrastructure for analysis and reporting by all stakeholders and the possibility of(More)
Data merging is an essential part of ETL (Extract-Transform-Load) processes to build a data warehouse system. To avoid rewheeling merging techniques, we propose a Data Merging Meta-model (DMM) and its transformation into executable program codes in the manner of model driven engineering. DMM allows defining relationships of different model entities and(More)
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