IRIT at TREC Knowledge Base Acceleration 2013: Cumulative Citation Recommendation Task

Abstract : This paper describes the IRIT lab participation to the Cumulative Citation Recommendation task of the TREC 2013 Knowledge Base Acceleration Track. In this task, we are asked to implement a system which aims to detect “Vital” documents that a human would want to cite when updating the Wikipedia article for the target entity. Our approach is built on two steps. First, for each topic (entity), we retrieve a set of potential relevant documents containing at least one entity mention. These documents are then classified using a supervised learning algorithm to identify which ones are vital. We submitted three runs using different combinations of features. Obtained results are presented and discussed.
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https://hal.archives-ouvertes.fr/hal-01143717
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  • HAL Id : hal-01143717, version 1
  • OATAO : 13017

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Rafik Abbes, Karen Pinel-Sauvagnat, Nathalie Hernandez, Mohand Boughanem. IRIT at TREC Knowledge Base Acceleration 2013: Cumulative Citation Recommendation Task. The Twenty-Second Text REtrieval Conference - TREC 2013, Nov 2013, Gaithersburg, United States. pp. 1-4. ⟨hal-01143717⟩

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