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In this paper we propose a novel method for automatically generating and recommending semantic tags for text documents, namely terms that reflect the intended meaning of the document in an accurate and complete way. Our approach is based on the utilization of existing domain knowledge, in the form of ontologies, and particularly in the selection and exploitation of those ontological relations that are most appropriate for the given tagging scenario and domain. Experimental evaluation of the method with significant number of documents and high volume of ontological knowledge shows a high level of accuracy as far as tag identification is concerned.