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

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2011) 6741 LNCS 436-451
DOI: 10.1007/978-3-642-21640-4_33
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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. © 2011 Springer-Verlag.

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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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6741 LNCS, pp. 436–451). https://doi.org/10.1007/978-3-642-21640-4_33

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