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Text Mining for Semantic Relations as a Support Base of a Scientific Portal Generator

Current Semantic Web implementation efforts pose a number of challenges. One of the big ones among them is development and evolution of specific resources --- the ontologies --- as a base for representation of the meaning of the web. This paper deals with the automatic acquisition of semantic relations from the text of scientific publications (journal articles, conference papers, project descriptions, etc.). We also describe the process of building of corresponding ontological resources and their application for semi--automatic generation of scientific portals. Extracted relations and ontologies are crucial for the structuring of the information at the portal pages, automatic classification of the presented documents as well as for personalisation at the presentation level. Besides a general description of the portal generating system, we give also a detailed overview of extraction of semantic relations in the form of a domain--specific ontology. The overview consists of presentation of an architecture of the ontology extraction system, description of methods used for mining of semantic relations and analysis of selected results and examples.