Paper Recommendation System: A Global and Soft Approach

Siwipa Pruitikanee 1 Lisa Di Jorio 2 Anne Laurent 2 Michel Sala 2
1 LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
2 TATOO - Fouille de données environnementales
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Paper recommendation to researchers has been extensively studied in the last years, and many methods have been investigated for this purpose. In this paper, we propose a novel approach embedding the whole process for selecting papers of interest given some keywords. Our approach is based on a workflow integrating fuzzy clustering of the papers, the computation of a representative summary paper per cluster using OWA operators, and ranking, in order to answer user queries adequately. The originality of our method relies in the introduction of fuzziness for more flexibility in the approach. The use of representative papers allows us to summarize sets of papers into a single representative one, thus simplifying the users interactions with the huge number of papers from the literature.
Keywords : Soft Computing Recommandation Fuzzy Clustering OWA
Type de document :
Communication dans un congrès
FUTURE COMPUTING, Jun 2012, Nice, France. 4th International Conference on Future Computational Technologies and Applications, 2012
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Contributeur : Anne Laurent <>
Soumis le : samedi 23 mars 2013 - 21:16:16
Dernière modification le : vendredi 19 octobre 2018 - 01:14:12
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Siwipa Pruitikanee, Lisa Di Jorio, Anne Laurent, Michel Sala. Paper Recommendation System: A Global and Soft Approach. FUTURE COMPUTING, Jun 2012, Nice, France. 4th International Conference on Future Computational Technologies and Applications, 2012. 〈lirmm-00803915〉

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