Research In Motion
In knowledge-discovery and data mining, the method of finding huge volumes of data for patterns using tools such as categorization, clustering, etc. is very common. The data thus has received too many parameters. For someone who is a non skilled in data mining, the obtained policy are too far away, many of them non-fascinating and with low unambiguousness and very hard to recognize. To overcome these limitations of simple keyword and content-based textual information access, an ontology-driven framework is developed.