ONTECTAS: bridging the gap between collaborative tagging systems and structured data

Authors:
Ali Moosavi;Tianyu Li;Laks V. S. Lakshmanan;Rachel Pottinger
Affiliations:
University of British Columbia, Vancouver, BC, Canada;University of British Columbia, Vancouver, BC, Canada;University of British Columbia, Vancouver, BC, Canada;University of British Columbia, Vancouver, BC, Canada
Venue:
CAiSE'11 Proceedings of the 23rd international conference on Advanced information systems engineering
Year:
2011

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Abstract

Ontologies define a set of terms and the relationships (e.g., is-a and has-a) between them; they are the building block of the emerging semantic web. An ontology relating the tags in a collaborative tagging system (CTS) makes the CTS easier to understand. We propose an algorithm to automatically construct an ontology from CTS data and conduct a detailed empirical comparison with previous related work on four real data sets - Del.icio.us, LibraryThing, CiteULike, and IMDb. We also verify the effectiveness of our algorithm in detecting is-a and has-a relationships.