Semi-supervised image meta-filtering in cultural heritage applications Semi-supervised image meta-filtering in cultural heritage applications Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2015-11-042014enAn image filtering scheme for images of cultural interest is presented. The model utilize a semi supervised approach for the creation of an appropriate distance learning metric, which is used for the filtering. User’s feedback is involved only for a minor set of data, defined using optics algorithm and sparse modeling representative selection. Such approach facilitates the refinement of retrieval results always under the scope of the end user needs.http://creativecommons.org/licenses/by/4.0/102-1105th International Conference Matsatsinis Nikolaos Ματσατσινης Νικολαος Doulamis, Anastasios Eftychios Protopapadakis Springer Verlag Clustering, Document document clustering clustering document Learning, Supervised (Machine learning) supervised learning machine learning learning supervised machine learning