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Formulation of suitable search expressions for information retrieval from large full-text databases may currently require considerable e orts. Changing the scope of the search when, eg, too many or too few hits have been obtained, requires re-formulation of the search expression. For an alternative scheme we suggest an explorative full-text information retrieval method, where the Self-Organizing Map (SOM) algorithm is used to order documents based on their full textual contents. The visualized order can then be utilized for an explorative search or exploration of novel knowledge areas, whereby the scope can be changed interactively. The ordering of the documents is achieved by a two-level analysis: First, word categories are extracted from the text by a\semantic" SOM. Second, the textual context of the documents is encoded on the basis of the histograms of words formed on the word category map.