| Téléchargement | - Voir le manuscrit accepté : Incorporating Prior Knowledge into a Transductive Ranking Algorithm for Multi-Document Summarization (PDF, 566 Kio)
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| DOI | Trouver le DOI : https://doi.org/10.1145/1571941.1572087 |
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| Auteur | Rechercher : Amini, Massih-Reza1; Rechercher : Usunier, Nicolas |
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| Affiliation | - Conseil national de recherches du Canada. Institut de technologie de l'information du CNRC
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| Format | Texte, Article |
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| Conférence | (SIGIR '09) The 32nd International ACM SIGIR Conference on research and development in Information Retrieval(SIGIR '09), Boston, MA, USA, July 19-23, 2009 |
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| Sujet | Information and Communications Technologies |
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| Résumé | This paper presents a transductive approach to learn ranking functions for extractive multi-document summarization. At the first stage, the proposed approach identifies topic themes within a document collection, which help to identify two sets of relevant and irrelevant sentences to a question. It then iteratively trains a ranking function over these two sets of sentences by optimizing a ranking loss and fitting a prior model built on keywords. The output of the function is used to find further relevant and irrelevant sentences. This process is repeated until a desired stopping criterion is met. |
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| Date de publication | 2009 |
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| Dans | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Numéro NPARC | 16067309 |
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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 | e5d0c574-452d-417c-bea4-4fec9cbb8a7a |
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| Enregistrement créé | 2010-09-10 |
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| Enregistrement modifié | 2020-04-16 |
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