Inducing Ontologies from Folksonomies using Natural Language Understanding

Marta Tatu, Dan Moldovan


Abstract
Folksonomies are unsystematic, unsophisticated collections of keywords associated by social bookmarking users to web content and, despite their inconsistency problems (typographical errors, spelling variations, use of space or punctuation as delimiters, same tag applied in different context, synonymy of concepts, etc.), their popularity is increasing among Web 2.0 application developers. In this paper, in addition to eliminating folksonomic irregularities existing at the lexical, syntactic or semantic understanding levels, we propose an algorithm that automatically builds a semantic representation of the folksonomy by exploiting the tags, their social bookmarking associations (co-occuring tags) and, more importantly, the content of labeled documents. We derive the semantics of each tag, discover semantic links between the folksonomic tags and expose the underlying semantic structure of the folksonomy, thus, enabling a number of information discovery and ontology-based reasoning applications.
Anthology ID:
L10-1136
Volume:
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)
Month:
May
Year:
2010
Address:
Valletta, Malta
Editors:
Nicoletta Calzolari, Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Mike Rosner, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2010/pdf/203_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Marta Tatu and Dan Moldovan. 2010. Inducing Ontologies from Folksonomies using Natural Language Understanding. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), Valletta, Malta. European Language Resources Association (ELRA).
Cite (Informal):
Inducing Ontologies from Folksonomies using Natural Language Understanding (Tatu & Moldovan, LREC 2010)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2010/pdf/203_Paper.pdf