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Supervised Learning Methods for Diversification of Image Search Results
We adopt a supervised learning framework, namely R-LTR [17], to diversify image search results, and extend it in various ways. Our experiments show that the adopted and proposed variants are superior to two well-known baselines, with relative gains up to 11.4%.
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| Publicado no: | Advances in Information Retrieval |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7148049/ https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-45442-5_20 |
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