A NOVEL ONTOLOGY TOOL FOR DATA CLEANING

Researchers develop data extractor which could effectively extract data from web sources, tabulate them, and used it for further processing. However, not all data are correctly extracted, they may either missed certain valuable information or contain additional unnecessary information. In the case of unnecessary information, researchers use a cleaning method to remove them such that the data extracted are free of errors. Removing these data is important as unnecessary information may affect the accuracy of subsequent extractor tools, hence may eventually prevent the tool from performing its task efficiently. In this research proposal, we embark on a data cleaning tool to clean data using ontology tools, which could effectively clean data based on their semantics. Experimental results show that our tool is highly efficient in data cleaning and is able to outperform existing state of the art tools.