Growing hierarchical self-organizing map for searching documents using visual content

This paper presents document search model based on its visual content. There is used hierarchical clustering algorithm — GHSOM. Description of proposed model is given as learning and searching phase. Also some experiments are described on benchmark image sets (e.g. ICPR, MIRFlickr) and created document set. Paper presents some experiments connected with document measures and their influence on searching results. Also in this paper some first results are given and directions of further research are given.