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High Performance Query-by-Example Keyword Spotting Using Query-by-String Techniques. 13th International Conference on Document Analysis and Recognition, 2015. IEEE Computer Society.Keyword Spotting (KWS) has been traditionally considered under two distinct frameworks: Query-by-Example (QbE) and Query-by-String (QbS). In both cases, the user of the system wished to find occurrences of a particular keyword in a collection of document images. The difference is that, in QbE the keyword is given as an exemplar image while, in the case of QbS, the keyword is given as a text string. In several works, the QbS scenario has been approached using QbE techniques; but the converse has not been studied in depth yet, despite of the fact that QbS systems typically achieve higher accuracy. In the present work, we present a very effective probabilistic approach for QbE KWS, based on highly accurate QbS KWS techniques. To assess the effectiveness of this approach, we tackle the segmentation-free QbE task of the ICFHR-2014 Competition on Handwritten KWS. Our approach achieves a mean average precision (mAP) as high as 0.715, which improves by more than 70% the best mAP achieved in this competition (0.419 under the same experimental conditions).