Abstract
In this paper, we present a Wikipedia-based approach to query expansion for the task of image retrieval, by combining salient encyclopaedic concepts with the picturability of words. Our model generates the expanded query terms in a definite two-stage process instead of multiple iterative passes, requires no manual feedback, and is completely unsupervised. Preliminary results show that our proposed model is effective in a comparative study on the ImageCLEF 2010 Wikipedia dataset.
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Savenkov, D., Braslavski, P., Lebedev, M. (2011). Search Snippet Evaluation at Yandex: Lessons Learned and Future Directions. In: Forner, P., Gonzalo, J., Kekäläinen, J., Lalmas, M., de Rijke, M. (eds) Multilingual and Multimodal Information Access Evaluation. CLEF 2011. Lecture Notes in Computer Science, vol 6941. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23708-9_4
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DOI: https://doi.org/10.1007/978-3-642-23708-9_4
Publisher Name: Springer, Berlin, Heidelberg
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