DocumentCode
1868272
Title
Are Clickthroughs Useful for Image Labelling?
Author
Ashman, Helen ; Antunovic, Michael ; Donner, Christoph ; Frith, Rebecca ; Rebelos, Eric ; Schmakeit, Jan-Felix ; Smith, Gavin ; Truran, Mark
Volume
1
fYear
2009
fDate
15-18 Sept. 2009
Firstpage
191
Lastpage
197
Abstract
In this paper we look at how images can be labelled as a result of click throughs from searches. One approach acts as a filter on image searches specifically, while the other approach propagates labels to images from their containing pages, where those pages were labelled themselves using clickthrough as a filter on text search. Then the paper reports on an experiment where users ranked for relevance six methods for labelling images, comparing the two clickthrough-based methods with flickr´s amateur explicit labelling, Getty´s professional explicit labelling, Google´s standard image search, and the new Google Image Labeller. As well as comparing the accuracy of the proposed image labelling methods and discovering that automatic methods outperform explicit human labelling methods, the experiment suggests clickthrough data is reliable with very few clicks for image classification purposes.
Keywords
Australia; Conferences; Electronic mail; Filters; Humans; Image classification; Information science; Intelligent agent; Labeling; Search engines;
fLanguage
English
Publisher
iet
Conference_Titel
Web Intelligence and Intelligent Agent Technologies, 2009. WI-IAT '09. IEEE/WIC/ACM International Joint Conferences on
Conference_Location
Milan, Italy
Print_ISBN
978-0-7695-3801-3
Electronic_ISBN
978-1-4244-5331-3
Type
conf
DOI
10.1109/WI-IAT.2009.35
Filename
5286074
Link To Document