Pattern Matching Techniques to Improve Folksonomies Quality Grouping Synstactic Variations of Tags – ITA 2009

Abstract

Folksonomies have emerged as a popular way of annotating and categorizing content using a set of tags that are created and managed in a collaborative way. The appeal of folksonomies comes from the fact that they require a low effort for creation and maintenance since they are community-generated. However they present important drawbacks regarding their limited navigation 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 syntactic variations of a same tag. This paper focuses on the use of different pattern matching techniques in order to improve folksonomies quality by grouping syntactic variations of tags. We propose the utilization of fuzzy similarity measures, comparing this proposal with other classical pattern matching techniques, and we conclude that this technique offers better results than other classic techniques after comparing them on a large real dataset.

Authors

Francisco Echarte, José Javier Astrain, Alberto Córdoba and Jesús Villadangos

Data

• Excel file with tags similarities: download

Reference

Echarte, F., Astrain, J.J., Córdoba, A., Villadangos, J.: Pattern Matching Techniques to Improve Folksonomies Quality Grouping Synstactic Variations of Tags, Third International Conference on Internet Techonologies & Applications, ITA09. Wrexham, North Wales, UK, 2009.