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Nicky Ransom University for the Creative Arts

Nicky Ransom University for the Creative Arts. Tags William Hall Raine crowd men hats street night lighting faces sea of people people watching event election results populated. Election night crowd, Wellington, 1931

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Nicky Ransom University for the Creative Arts

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  1. Nicky Ransom University for the Creative Arts

  2. Tags • William Hall Raine • crowd • men • hats • street • night • lighting • faces • sea of people • people • watching • event • election • results • populated Election night crowd, Wellington, 1931 Photographer: William Hall RaineElection night crowd, Wellington, 1931Reference number: 1/2-066547-FOriginal negative Photographic Archive, Alexander Turnbull Library

  3. Growth in number of images online • Accurate and comprehensive indexing is critical to make online content accessible • But visual materials are difficult to index

  4. Concept-based indexing – assigning index terms to describe the subject of an image

  5. Concept-based indexing – assigning index terms to describe the subject of an image • Search engine indexing – index terms automatically created from data related to an image

  6. Concept-based indexing – assigning index terms to describe the subject of an image • Search engine indexing – index terms automatically created from data related to an image • Content-based indexing – using automatic processing to index image attributes such as colour, texture and shape

  7. CIRES: Content Based Image REtrieval System

  8. To find out value of tags for image retrieval by investigating whether the terms used to describe images in tags are similar to the terms used to search for images. • Which image facets are described in user tags? • How do these compare to those found in image queries? • What are the implications for future use of tagging for online indexing?

  9. Armitage, L., & Enser, P. (1997). Analysis of user need in image archives Journal of Information Science, 23(4), 287-299.

  10. Small scale study using 250 images and associated tags on Flickr • Tags categorised using facets from ‘Shatford’s matrix’ • Comparisons made with results of previous research into user queries

  11. Limited sample size – only 250 images • Use of Flickr as domain for study – only 38% of users apply tags • Subjectivity of categorising tags – only one person assigning tags to categories • Suitability of Shatford’s matrix – 22% of terms could not be categorised • Lack of online query studies with which to compare the results

  12. Broad similarities between the image facets used in queries and image tags • But differences in the level of specificity • Need to develop systems to bridge this gap • Consider the value of tags for browsing systems

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