Automatic keywords extraction - a basis for content recommendation
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AbstractThis paper describes a use case for an application that recommends learning objects for reuse and is integrated in the authoring environment. The recommendations are based on the automatic detection of content being authored and the context in which this resource is authored or used. The focus of the paper is automatic keyword extraction, evaluated as a starting point for content analysis. The evaluations explore whether automatic keyword extraction from content being authored is a sound basis for recommending relevant learning objects. The results show that automatically extracted keywords are suitable for this purpose, if some observed issues are appropriately addressed.