document: Image annotation using clickthrough data Automatic image annotation using supervised learning is performed by concept classifiers trained on labeled example images . This work proposes the use of clickthrough data collected from search logs as a source for the automatic generation of concept training data , thus avoiding the expensive manual annotation effort . We investigate and evaluate this approach using a collection of 97,628 photographic images . The results indicate that the contribution of search log based training data is positive ; in particular , the combination of manual and automatically generated training data outperforms the use of manual data alone . It is therefore possible to use clickthrough data to perform large-scale image annotation with little manual annotation effort or , depending on performance , using only the automatically generated training data . The datasets used as well as an extensive presentation of the experimental results can be accessed at http:\/\/olympus.ee.auth.gr\/~diou\/civr2009\/ .
doc_bio_tags: B I O B I O B I O B I O O O O O O O O O O O O O O O O O B I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O