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Modelling what users see when they look at images: a cognitive viewpoint

Howard Greisdorf (Texas Center for Digital Knowledge, University of North Texas, Denton, Texas, USA)
Brian O’Connor (Texas Center for Digital Knowledge, University of North Texas, Denton, Texas, USA)

Journal of Documentation

ISSN: 0022-0418

Article publication date: 1 February 2002

2466

Abstract

Analysis of user viewing and query‐matching behavior furnishes additional evidence that the relevance of retrieved images for system users may arise from descriptions of objects and content‐based elements that are not evident or not even present in the image. This investigation looks at how users assign pre‐determined query terms to retrieved images, as well as looking at a post‐retrieval process of image engagement to user cognitive assessments of meaningful terms. Additionally, affective/emotion‐based query terms appear to be an important descriptive category for image retrieval. A system for capturing (eliciting) human interpretations derived from cognitive engagements with viewed images could further enhance the efficiency of image retrieval systems stemming from traditional indexing methods and technology‐based content extraction algorithms. An approach to such a system is posited.

Keywords

Citation

Greisdorf, H. and O’Connor, B. (2002), "Modelling what users see when they look at images: a cognitive viewpoint", Journal of Documentation, Vol. 58 No. 1, pp. 6-29. https://doi.org/10.1108/00220410210425386

Publisher

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MCB UP Ltd

Copyright © 2002, MCB UP Limited

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