A conceptual design of a web information extraction and data analysis learning framework

The Web is flooded with data. However, there is a huge gap between data and information. Collecting, normalization, and analyzation are required steps to transform data into information. However, HTML is document-centric rather than data-centric. Extracting large amounts of data from the Web is a time consuming and tedious task, but information technologies can only provide little help, especially when users lack of domain knowledge. In this research, the conceptual design of a Web information extraction and data analysis framework is proposed. The framework helps data analysts go through the required steps. Furthermore, our design is suitable for inexperienced beginners in data analyzation field since some assistant modules have been considered.