%0 Conference Proceedings %T A Kernel-based Approach to Document Retrieval %A Albert Gordo %A Jaume Gibert %A Ernest Valveny %A Marçal Rusiñol %B 9th IAPR International Workshop on Document Analysis Systems %D 2010 %@ 978-1-60558-773-8 %F Albert Gordo2010 %O DAG %O exported from refbase (http://refbase.cvc.uab.es/show.php?record=1431), last updated on Mon, 15 May 2017 10:19:06 +0200 %X In this paper we tackle the problem of document image retrieval by combining a similarity measure between documents and the probability that a given document belongs to a certain class. The membership probability to a specific class is computed using Support Vector Machines in conjunction with similarity measure based kernel applied to structural document representations. In the presented experiments, we use different document representations, both visual and structural, and we apply them to a database of historical documents. We show how our method based on similarity kernels outperforms the usual distance-based retrieval. %U http://dx.doi.org/10.1145/1815330.1815379 %P 377–384