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FoldCons: A Simple Way To Improve Tag Recommendation

Modou Gueye Talel Abdessalem 1 Hubert Naacke 2 
1 DBWeb
LTCI - Laboratoire Traitement et Communication de l'Information
2 BD - Bases de Données
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : Tag recommendation is a major aspect of collaborative tagging systems. It aims to recommend tags to a user for tagging an item. In this paper we present a part of our work in progress which is a novel improvement of recommendations by re-ranking the output of a tag recommender. We mine association rules between candidates tags in order to determine a more consistent list of tags to recommend. Our method is an add-on one which leads to better recommendations as we show in this paper. It is easily parallelizable and morever it may be applied to a lot of tag recommenders. The experiments we did on five datasets with two kinds of tag recommender demonstrated the efficiency of our method.
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Contributor : Modou Gueye Connect in order to contact the contributor
Submitted on : Wednesday, December 4, 2013 - 2:40:22 PM
Last modification on : Sunday, June 26, 2022 - 9:53:54 AM


  • HAL Id : hal-00913859, version 1


Modou Gueye, Talel Abdessalem, Hubert Naacke. FoldCons: A Simple Way To Improve Tag Recommendation. 5th ACM RecSys Workshop on Recommender Systems & the Social Web, Oct 2013, Hong Kong, Hong Kong SAR China. pp.Session: Tags. ⟨hal-00913859⟩



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