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Communication Dans Un Congrès Année : 2011

The importance of the depth for text-image selection strategy in Learning to Rank

Résumé

We examine the effect of the number documents being pooled, for constructing training sets, has on the performance of the learning-to-rank (LTR) approaches that use it to build our ranking functions. Our investigation takes place in a multimedia setting and uses the ImageCLEF photo 2006 dataset based on text and visual features. Experiments show that our LTR algorithm, OWPC,outperforms other baselines.

Dates et versions

hal-01284773 , version 1 (08-03-2016)

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David Buffoni, Sabrina Tollari, Patrick Gallinari. The importance of the depth for text-image selection strategy in Learning to Rank. European Conference on Information Retrieval (ECIR 2011), Apr 2011, Dublin, Ireland. pp.743-746, ⟨10.1007/978-3-642-20161-5_84⟩. ⟨hal-01284773⟩
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