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EnTag: enhancing social tagging for discovery
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International Conference on Digital Libraries archive
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries table of contents
Austin, TX, USA
SESSION: 6: best paper nominees 2 table of contents
Pages: 163-172  
Year of Publication: 2009
ISBN:978-1-60558-322-8
Authors
Koraljka Golub  University of Bath, Bath, United Kingdom
Jim Moon  University of Glamorgan, Pontypridd, United Kingdom
Douglas Tudhope  University of Glamorgan, Pontypridd, United Kingdom
Catherine Jones  STFC Rutherford Appleton Laboratory, Chilton, Didcot, United Kingdom
Brian Matthews  STFC Rutherford Appleton Laboratory, Chilton, Didcot, United Kingdom
BartBomiej PuzoD  STFC Rutherford Appleton Laboratory, Chilton, Didcot, United Kingdom
Marianne Lykke Nielsen  Royal School of Library and Information Science, Aalborg, Denmark
Sponsors
SIGIR: ACM Special Interest Group on Information Retrieval
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
Koraljka Golub: colleagues
Jim Moon: colleagues
Douglas Tudhope: colleagues
Catherine Jones: colleagues
Brian Matthews: colleagues
BartBomiej PuzoD: colleagues
Marianne Lykke Nielsen: colleagues