EnTag: enhancing social tagging for discovery

  • Authors:
  • Koraljka Golub;Jim Moon;Douglas Tudhope;Catherine Jones;Brian Matthews;BartBomiej PuzoD;Marianne Lykke Nielsen

  • Affiliations:
  • University of Bath, Bath, United Kingdom;University of Glamorgan, Pontypridd, United Kingdom;University of Glamorgan, Pontypridd, United Kingdom;STFC Rutherford Appleton Laboratory, Chilton, Didcot, United Kingdom;STFC Rutherford Appleton Laboratory, Chilton, Didcot, United Kingdom;STFC Rutherford Appleton Laboratory, Chilton, Didcot, United Kingdom;Royal School of Library and Information Science, Aalborg, Denmark

  • Venue:
  • Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
  • Year:
  • 2009

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Abstract

The EnTag (Enhanced Tagging for Discovery) project investigated the effect on indexing and retrieval when using only social tagging versus when using social tagging in combination with suggestions from a controlled vocabulary. Two different contexts were explored: tagging by readers of a digital collection and tagging by authors in an institutional repository; also two different controlled vocabularies were examined, Dewey Decimal Classification and ACM Computing Classification Scheme. For each context a separate demonstrator was developed and a user study conducted. The results showed the importance of controlled vocabulary suggestions for both indexing and retrieval: to help produce ideas of tags to use, to make it easier to find focus for the tagging, as well as to ensure consistency and increase the number of access points in retrieval. The value and usefulness of the suggestions proved to be dependent on the quality of the suggestions, both in terms of conceptual relevance to the user and in appropriateness of the terminology. The participants themselves could also see the advantages of controlled vocabulary terms for retrieval if the terms used were from an authoritative source.