Improving folksonomies quality by syntactic tag variations grouping

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.

REFERENCES

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Information filtering

General Terms:
Design, Experimentation, Measurement, Performance

Keywords:
folksonomies, fuzzy logic, pattern matching, semantic web