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.
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Moosavi, A., Li, T., Lakshmanan, L.V.S., Pottinger, R. (2011). ONTECTAS: Bridging the Gap between Collaborative Tagging Systems and Structured Data. In: Mouratidis, H., Rolland, C. (eds) Advanced Information Systems Engineering. CAiSE 2011. Lecture Notes in Computer Science, vol 6741. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21640-4_33
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