Hierarchical Categorisation of Web Tags for Delicious

ion that enables us to conclude, directly from the inspection of the user profile, that these users are interested in politics. In this sense, the categorization of tags allows us represent user profiles in a tractable manner, on the basis a reduced set of meaningful categories of interest. Motivated by this, next we proceed to describe the methodology that we followed to categorise the Delicious data set retrieved by the Distributed Artificial Intelligence Laboratory (DAILabor), at Technische Universität Berlin [1]. This methodology, explained in what follows, is in line with other works in this field [2], [3]. The data set in question is organized in the form of triples (username, bookmark, tag), each one modelling the action of a user associating a bookmark with a tag. To accomplish J. Parra Arnau, J. Forné and D. Rebollo-Monedero are with the Department of Telematics Engineering, Universitat Politècnica de Catalunya, C.\ Jordi Girona 1-3, E-08034 Barcelona, Catalonia. E-mail: {javier.parra,jforne,david.rebollo}@entel.upc.edu A. Perego is with the Institute for Environment and Sustainability of the Joint Research Centre, European Commission, I-21027 Ispra, Italy. E-mail: [email protected]. E. Ferrari is with the Department of Theoretical and Applied Science, University of Insubria, Via Mazzini 5, I-21100 Varese, Italy. E-mail: [email protected]. HIERARCHICAL CATEGORISATION OF WEB TAGS FOR DELICIOUS 2/23 this categorisation, first we carried out some preprocessing to filter out those tags considered as spam. For this purpose, we collected some statistics about the number of characters contained by tags. After observing that 98% of tags had less than 23 characters, we dropped those tags with a number of characters over 22. In addition, we eliminated those posts with more than 50 tags, as they are usually spam [2]. Additionally, posts with no tags were not considered. After this simple preprocessing, the number of triples reduced to 1,149,895, and, consequently, the number of users, bookmarks and tags to 9,207, 349,658 and 54,024,