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Does organisation by similarity assist image browsing?
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Source Conference on Human Factors in Computing Systems archive
Proceedings of the SIGCHI conference on Human factors in computing systems table of contents
Seattle, Washington, United States
Pages: 190 - 197  
Year of Publication: 2001
ISBN:1-58113-327-8
Authors
Kerry Rodden  University of Cambridge Computer Laboratory, Pembroke Street, Cambridge CB2 3QG, UK
Wojciech Basalaj  University of Cambridge Computer Laboratory, Pembroke Street, Cambridge CB2 3QG, UK
David Sinclair  AT&T Laboratories Cambridge, Trumpington Street, Cambridge CB2 1QA, UK
Kenneth Wood  AT&T Laboratories Cambridge, Trumpington Street, Cambridge CB2 1QA, UK
Sponsor
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
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ABSTRACT

In current systems for browsing image collections, users are presented with sets of thumbnail images arranged in some default order on the screen. We are investigating whether it benefits users to have sets of thumbnails arranged according to their mutual similarity, so images that are alike are placed together. There are, of course, many possible definitions of “similarity”: so far we have explored measurements based on low-level visual features, and on the textual captions assigned to the images. Here we describe two experiments, both involving designers as the participants, examining whether similarity-based arrangements of the candidate images are helpful for a picture selection task. Firstly, the two types of similarity-based arrangement were informally compared. Then, an arrangement based on visual similarity was more formally compared with a control of a random arrangement. We believe this work should be of interest to anyone designing a system that involves presenting sets of images to users.


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.

 
1
Armitage, L.H., and Enser, P.G.B. Analysis of user need in image archives. Journal of Information Science 23(4), 1997, 287-299.
 
2
Basalaj, W. Proximity visualisation of abstract data. PhD thesis, University of Cambridge Computer Laboratory, 2000.
 
3
Borg, I., and Groenen, P. Modern multidimensional scaling. New York: Springer-Verlag, 1997.
 
4
Borlund, P., and Ingwersen, P. The development of a method for the evaluation of interactive information retrieval systems. Journal of Documentation 53(3), 1997, 225-250.
5
 
6
Chen, C, and Czerwinski, M. Spatial ability and visual navigation: an empirical study. The New Review of Hypermedia and Multimedia, 3, 67-89.
7
8
9
 
10
Leuski, A., and Allan, J. Improving interactive retrieval by combining ranked lists and clustering. Proc. RIAO 2000.
 
11
 
12
Raven, J.C. Raven's Advanced Progressive Matrices. Psychological Corporation, http://www.psychcorp.com.
 
13
Rodden, K. Evaluating user interfaces for image browsing and retrieval. PhD thesis, University of Cambridge Computer Laboratory, 2001.
 
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Rose, T., Elworthy, D., Kotcheff, A., Clare, A., and Tsonis, P. ANVIL: a system for the retrieval of captioned images using NLP techniques. Proc. CIR2000, BCS (http://www.ewic.org.uk), 2000.
 
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CITED BY  45

Collaborative Colleagues:
Kerry Rodden: colleagues
Wojciech Basalaj: colleagues
David Sinclair: colleagues
Kenneth Wood: colleagues