Weighted Self-Organizing Maps: Incorporating User Feedback

Abstract : One interesting way of accessing collections of multimedia objects is by methods of visualization and clustering. Growing self-organizing maps provide such a solution, which adapts automatically to the underlying database. Unfortunately, the result of the clustering greatly depends on the definition of the describing features and the used similarity measure. In this paper, we present a general approach to improve the obtained clustering by incorporating user feedback (in the form of drag-and-drop) into the underlying topology of the self-organizing map.
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Andreas Nürnberger, Marcin Detyniecki. Weighted Self-Organizing Maps: Incorporating User Feedback. ICANN 2003 - International Conference on Artificial Neural Networks, Jun 2003, Istanbul, Turkey. pp.883-890, ⟨10.1007/3-540-44989-2_105⟩. ⟨hal-01533236⟩



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