Francisco Echarte
ABSTRACT
Folksonomies offer an easy method to organize information in the current Web. This fact and their collaborative features have derived in an extensive involvement in many Social Web projects. However they present important drawbacks regarding their limited exploring and searching capabilities, in contrast with other methods as taxonomies, thesauruses and ontologies. One of these drawbacks is an effect of its flexibility for tagging, producing frequently multiple variations of a same tag. In this paper we propose a method to group syntactic variations of tags using pattern matching techniques. We propose the utilization of a fuzzy similarity measure and we conclude that this technique offers better results than other classic techniques after comparing them on a large real dataset.
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Digital Library
- Echarte, F., Astrain, J. J., Córdoba, A., Villadangos, J.: Ontology of Folksonomy: A New Modeling Method. In SAAKM 2007, (Whistler, Canada, October 28--31, 2007).Google Scholar
- Garitagoitia, J. R., González de Mendívil, J. R., Echanobe, J., Astrain, J. J., Fariña, F.: Deformed Fuzzy Automata for Correcting Imperfect Strings of Fuzzy Symbols, IEEE Transactions on Fuzzy Systems, 11, 3 (2003), 299--310. Google ScholarDigital Library
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- Vander Wal, T.: Folksonomy, http://vanderwal.net/folksonomy.htmlGoogle Scholar
Index Terms
- Improving folksonomies quality by syntactic tag variations grouping
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