We consider in depth the semantic analysis in learning systems as well as some information retrieval techniques applied for measuring the document similarity in eLearning. These results are obtained in a CALL project, which ended by extensive user evaluation. After several years spent in the development of CALL modules and prototypes, we think that much closer cooperation with real teaching experts is necessary, to find the proper learning niches and suitable wrappings of the language technologies, which could give birth to useful eLearning solutions.
Internet content today is about 80% text-based. No matter static or dynamic, the information is encoded and presented as multilingual, unstructured natural language text pages. As the Semantic Web aims at turning Internet into a machine-understandable resource, it becomes important to consider the natural language content and to assess the feasibility and the innovation of the semantic-based approaches related to unstructured texts. This paper reports about work in progress, an experiment in semantic based annotation and explores scenarios for application of Semantic Web techniques to the textual pages in Internet.
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