Semantic contextualisation of social tag-based profiles and item recommendations
EntityUAM. Departamento de Ingeniería Informática
PublisherSpringer Berlin Heidelberg
10.1007/978-3-642-23014-1_9E-Commerce and Web Technologies: 12th International Conference, EC-Web 2011, Toulouse, France, August 30 - September 1, 2011. Proceedings. Lecture Notes in Business Information Processing, Volumen 85. Springer, 2002. 101-113.
ISBN978-3-642-23013-4 (print); 978-3-642-23014-1 (online)
Funded byThis work was supported by the Spanish Ministry of Science and Innovation (TIN2008-06566-C04-02), and the Community of Madrid (CCG10- UAM/TIC-5877)
SubjectsAmbiguity; Clustering; Folksonomy; Recommender systems; Semantic contextualisation; Social tagging; User modelling; Informática
NoteProceedigns of 12th International Conference, EC-Web 2011, Toulouse, France, August 30 - September 1, 2011.
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-23014-1_9
Rights© Springer-Verlag Berlin Heidelberg 2011
We present an approach that efficiently identifies the semantic meanings and contexts of social tags within a particular folksonomy, and exploits them to build contextualised tag-based user and item profiles. We apply our approach to a dataset obtained from Delicious social bookmarking system, and evaluate it through two experiments: a user study consisting of manual judgements of tag disambiguation and contextualisation cases, and an offline study measuring the performance of several tag-powered item recommendation algorithms by using contextualised profiles. The results obtained show that our approach is able to accurately determine the actual semantic meanings and contexts of tag annotations, and allow item recommenders to achieve better precision and recall on their predictions.
Google Scholar:Cantador Gutiérrez, Iván - Bellogin Kouki, Alejandro - Fernández-Tobías, Ignacio - López-Hernández, Sergio
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