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Improving on Popularity as a Proxy for Generality When Building Tag Hierarchies from Folksonomies

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Social Informatics (SocInfo 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8851))

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  • International Conference on Social Informatics

Abstract

Building taxonomies for Web content manually is costly and timeconsuming. An alternative is to allow users to create folksonomies: collective social classifications. However, folksonomies have inconsistent structures and their use for searching and browsing is limited. Approaches have been proposed for acquiring implicit hierarchical structures from folksonomies, but these approaches suffer from the “generality-popularity” problem, in that they assume that popularity is a proxy for generality (that high level taxonomic terms will occur more often than low level ones). In this paper we test this assumption, and propose an improved approach (based on the Heymann-Benz algorithm) for tackling this problem by direction checking relations against a corpus of text. Our results show that popularity works as a proxy for generality in at most 77 of cases, but that this can be improved to 81% using our approach. This improvement will translate to higher quality tag hierarchy structures.

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Author information

Authors and Affiliations

  1. Electronics and Computer Science, University of Southampton, Southampton, United Kingdom

    Fahad Almoqhim, David E. Millard & Nigel Shadbolt

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  1. Fahad Almoqhim
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  2. David E. Millard
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  3. Nigel Shadbolt
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  1. Yahoo! Research, Barcelona, Spain

    Luca Maria Aiello

  2. Stanford Graduate School of Education, 485 Lasuen Mall, 94305-3096, Stanford, CA, USA

    Daniel McFarland

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Almoqhim, F., Millard, D.E., Shadbolt, N. (2014). Improving on Popularity as a Proxy for Generality When Building Tag Hierarchies from Folksonomies. In: Aiello, L.M., McFarland, D. (eds) Social Informatics. SocInfo 2014. Lecture Notes in Computer Science, vol 8851. Springer, Cham. https://doi.org/10.1007/978-3-319-13734-6_7

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  • DOI: https://doi.org/10.1007/978-3-319-13734-6_7

  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-13734-6

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