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Intellectual access to images image database systems [Electronic version
- Publisher
- Emerald Publishing
- Copyright
- Copyright © 2011 Emerald Group Publishing Limited. All rights reserved.
- ISSN
- 0022-0418
- DOI
- 10.1108/00220411111183582
- Publisher site
- See Article on Publisher Site
Abstract
Purpose – This study aims to consider the value of user‐assigned image tags by comparing the facets that are represented in image tags with those that are present in image queries to see if there is a similarity in the way that users describe and search for images. Design/methodology/approach – A sample dataset was created by downloading a selection of images and associated tags from Flickr, the online photo‐sharing web site. The tags were categorised using image facets from Shatford's matrix, which has been widely used in previous research into image indexing and retrieval. The facets present in the image tags were then compared with the results of previous research into image queries. Findings – The results reveal that there are broad similarities between the facets present in image tags and queries, with people and objects being the most common facet, followed by location. However, the results also show that there are differences in the level of specificity between tags and queries, with image tags containing more generic terms and image queries consisting of more specific terms. The study concludes that users do describe and search for images using similar image facets, but that measures to close the gap between specific queries and generic tags would improve the value of user tags in indexing image collections. Originality/value – Research into tagging has tended to focus on textual resources with less research into non‐textual documents. In particular, little research has been undertaken into how user tags compare to the terms used in search queries, particularly in the context of digital images.
Journal
Journal of Documentation – Emerald Publishing
Published: Oct 18, 2011
Keywords: Image retrieval; User tagging; Classification schemes; Data handling; Information retrieval