 | Up a level |
Group by: Item Type | No Grouping
Jump to: Conference or Workshop Item
Number of items: 2.
Conference or Workshop Item
An approach to building high-quality tag hierarchies from crowdsourced taxonomic tag pairs
http://jb4-2.eprints-hosting.org/2203
Building taxonomies for web content is costly. An alternative is to allow users to create folksonomies, collective social classifications. However, folksonomies lack structure and their use for searching and browsing is limited. Current approaches for acquiring latent hierarchical structures from folksonomies have had limited success. We explore whether asking users for tag pairs, rather than individual tags, can increase the quality of derived tag hierarchies. We measure the usability cost, and in particular cognitive effort required to create tag pairs rather than individual tags. Our results show that when applied to tag pairs a hierarchy creation algorithm (Heymann-Benz) has superior performance than when applied to individual tags, and with little impact on usability. However, the resulting hierarchies lack richness, and could be seen as less expressive than those derived from individual tags. This indicates that expressivity, not usability, is the limiting factor for collective tagging approaches aimed at crowdsourcing taxonomies
Fahad Almoqhim
David E. Millard
Nigel R Shadbolt
http://jb4-2.eprints-hosting.org/2203
Building taxonomies for web content is costly. An alternative is to allow users to create folksonomies, collective social classifications. However, folksonomies lack structure and their use for searching and browsing is limited. Current approaches for acquiring latent hierarchical structures from folksonomies have had limited success. We explore whether asking users for tag pairs, rather than individual tags, can increase the quality of derived tag hierarchies. We measure the usability cost, and in particular cognitive effort required to create tag pairs rather than individual tags. Our results show that when applied to tag pairs a hierarchy creation algorithm (Heymann-Benz) has superior performance than when applied to individual tags, and with little impact on usability. However, the resulting hierarchies lack richness, and could be seen as less expressive than those derived from individual tags. This indicates that expressivity, not usability, is the limiting factor for collective tagging approaches aimed at crowdsourcing taxonomies
Fahad Almoqhim
David E. Millard
Nigel R Shadbolt
Improving on popularity as a proxy for generality when building tag hierarchies from Folksonomies 6th International Conference, SocInfo 2014
http://jb4-2.eprints-hosting.org/2202
Building taxonomies for Web content manually is costly and time-consuming. 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.
Fahad Almoqhim
David E. Millard
Nigel Shadbolt
http://jb4-2.eprints-hosting.org/2202
Building taxonomies for Web content manually is costly and time-consuming. 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.
Fahad Almoqhim
David E. Millard
Nigel Shadbolt