An Integrated Framework to Enhance the Web Content Mining and Knowledge Discovery

This paper addresses the issue of distilling relevant information from unstructured data such as content from Web pages. For the purpose of solving this issue, a system is designed to propose a utilization of automated guided web mining algorithms for meta-rules extraction. The proposed system can be viewed as an extensible tool to extract metadata and generate multi-format descriptions from existing Web documents. The framework is evaluated on real web contents through two case studies: Acadian literature analysis and information on Canadian universities. The results show that the system easily provides meaningful visualizations and delivers powerful text extraction, supporting users in their quest to efficiently investigate and exploit available Web data sources.