Téléchargement | - Voir le manuscrit accepté : Multiview semi-supervised learning for ranking multilingual documents (PDF, 357 Kio)
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DOI | Trouver le DOI : https://doi.org/10.1007/978-3-642-23808-6_29 |
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Auteur | Rechercher : Usunier, Nicolas; Rechercher : Amini, Massih-Reza1; Rechercher : Goutte, Cyril1 |
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Affiliation | - Conseil national de recherches du Canada
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Format | Texte, Chapitre de livre |
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Conférence | European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2011). Athens, Greece. September 5-9, 2011 |
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Sujet | learning to rank; semi-supervised learning; multiview learning |
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Résumé | We address the problem of learning to rank documents in a multilingual context, when reference ranking information is only partially available. We propose a multiview learning approach to this semisupervised ranking task, where the translation of a document in a given language is considered as a view of the document. Although both multiview and semi-supervised learning of classifiers have been studied extensively in recent years, their application to the problem of ranking has received much less attention. We describe a semi-supervised multiview ranking algorithm that exploits a global agreement between viewspecific ranking functions on a set of unlabeled observations. We show that our proposed algorithm achieves significant improvements over both semi-supervised multiview classification and semi-supervised single-view rankers on a large multilingual collection of Reuters news covering 5 languages. Our experiments also suggest that our approach is most effective when few labeled documents are available and the classes are imbalanced. |
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Date de publication | 2011 |
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Maison d’édition | Springer Berlin Heidelberg |
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Dans | |
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Série | |
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Langue | anglais |
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Publications évaluées par des pairs | Non |
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Numéro NPARC | 18608906 |
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Exporter la notice | Exporter en format RIS |
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Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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Identificateur de l’enregistrement | cbacfa57-40f8-42ad-bf51-5e1417b443bf |
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Enregistrement créé | 2011-09-28 |
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Enregistrement modifié | 2020-03-03 |
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