Abstract
We can observe that the amount of non-toy domain ontologies is still
very limited for many areas of interest. In contrast, folksonomies are widely in
use for (1) tagging Web pages (e.g. del.icio.us), (2) annotating pictures (e.g.
flickr), or (3) classifying scholarly publications (e.g. bibsonomy). However,
such folksonomies cannot offer the expressivity of ontologies, and the
respective tags often lack a context-independent and intersubjective definition
of meaning. Also, folksonomies and other unsupervised vocabularies frequently
suffer from inconsistencies and redundancies. In this paper, we argue that the
social interaction manifested in folksonomies and in their usage should be
exploited for building and maintaining ontologies. Then, we sketch a
comprehensive approach for deriving ontologies from folksonomies by
integrating multiple resources and techniques. In detail, we suggest combining
(1) the statistical analysis of folksonomies, associated usage data, and their
implicit social networks, (2) online lexical resources like dictionaries, Wordnet,
Google and Wikipedia, (3) ontologies and Semantic Web resources, (4)
ontology mapping and matching approaches, and (5) functionality that helps
human actors in achieving and maintaining consensus over ontology element
suggestions resulting from the preceding steps.
Links and resources
Tags
community