Abstract
In this paper some results of a new text clustering methodology are presented. A prototype is an interesting document or a part of an extracted, interesting text. The given prototype is matched with the existing document database or the monitored document flow. Our claim is that the new methodology is capable of automatic content-based clustering using the information of the document. To verify this hypothesis an experiment was designed with the Bible. Four different translations, one Greek, one Latin, and two Finnish translations from years 1933/38 and 1992 were selected as test text material. Validation experiments were performed with a designed prototype version of the software application.
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Toivonen, J., Visa, A., Vesanen, T., Back, B., Vanharanta, H. (2001). Validation of Text Clustering Based on Document Contents. In: Perner, P. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 2001. Lecture Notes in Computer Science(), vol 2123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44596-X_15
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DOI: https://doi.org/10.1007/3-540-44596-X_15
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