Working Notes for the InFile Campaign : Online Document Filtering Using 1 Nearest Neighbor

Vincent Bodinier Ali Mustafa Qamar Eric Gaussier 1
1 MRIM - Modélisation et Recherche d’Information Multimédia [Grenoble]
LIG - Laboratoire d'Informatique de Grenoble, Inria - Institut National de Recherche en Informatique et en Automatique
Abstract : This paper has been written as a part of the InFile (INFormation, FILtering, Evaluation) campaign. This project is a cross-language adaptive filtering evaluation campaign, sponsored by the French national research agency, and it is a pilot track of the CLEF (Cross Language Evaluation Forum) 2008 campaigns. We propose in this paper an online algorithm to learn category specific thresholds in a multiclass environment where a document can belong to more than one class. Our method uses 1 Nearest Neighbor (1NN) algorithm for classification. It uses simulated user feedback to fine tune the threshold and in turn the classification performance over time. The experiments were run on English language corpus containing 100,000 documents. The best results have a precision of 0.366 and the recall is 0.260.
Type de document :
Communication dans un congrès
Workshop CLEF 2008, 2008, Aarhus, Denmark. 2008
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https://hal.inria.fr/hal-00954095
Contributeur : Marie-Christine Fauvet <>
Soumis le : vendredi 28 février 2014 - 16:13:05
Dernière modification le : jeudi 11 janvier 2018 - 06:22:06

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  • HAL Id : hal-00954095, version 1

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Vincent Bodinier, Ali Mustafa Qamar, Eric Gaussier. Working Notes for the InFile Campaign : Online Document Filtering Using 1 Nearest Neighbor. Workshop CLEF 2008, 2008, Aarhus, Denmark. 2008. 〈hal-00954095〉

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