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Leveraging Semantic Similarity for Folksonomy-Based Recommendation
Jan.-Feb. 2014 (vol. 18 no. 1)
pp. 48-55
Daniela Godoy, Argentinian National Scientific and Technical Research Council
Gustavo Rodriguez, Universidad Nacional del Centro de la Provincia de Buenos Aires
Franco Scavuzzo, Universidad Nacional del Centro de la Provincia de Buenos Aires
To recommend interesting resources such as webpages or pictures that are available through social tagging sites, recommender systems must be able to assess such resources' similarity to user profiles. Here, the authors analyze the role semantic similarity plays in calculating the resemblance between user profiles and published resources in folksonomies. Experiments carried out using data from two social sites show that associating semantics with tags results in more accurate similarities among elements in tagging systems and, consequently, enhances recommendations.
Index Terms:
Internet,Decision support systems,Semantics,Image processing,Handheld computers,Q measurement,Tagging,recommender systems,social tagging systems,folksonomies,similarity measures
Citation:
Daniela Godoy, Gustavo Rodriguez, Franco Scavuzzo, "Leveraging Semantic Similarity for Folksonomy-Based Recommendation," IEEE Internet Computing, vol. 18, no. 1, pp. 48-55, Jan.-Feb. 2014, doi:10.1109/MIC.2013.26
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