Applying information foraging theory to understand user interaction with content-based image retrieval

2.50
Hdl Handle:
http://hdl.handle.net/10547/297889
Title:
Applying information foraging theory to understand user interaction with content-based image retrieval
Authors:
Liu, Haiming; Mulholland, Paul; Song, Dawei; Uren, Victoria; Rüger, Stefan
Abstract:
The paper proposes an ISE (Information goal, Search strategy, Evaluation threshold) user classification model based on Information Foraging Theory for understanding user interaction with content-based image retrieval (CBIR). The proposed model is verified by a multiple linear regression analysis based on 50 users' interaction features collected from a task-based user study of interactive CBIR systems. To our best knowledge, this is the first principled user classification model in CBIR verified by a formal and systematic qualitative analysis of extensive user interaction data.
Citation:
Liu, H., Mulholland, P, Song, D., Uren, V. and Rüger, S. (2010) 'Applying information foraging theory to understand user interaction with content-based image retrieval', IIiX '10 Proceedings of the third symposium on Information interaction in context, pp. 135-144
Publisher:
ACM
Issue Date:
2010
URI:
http://hdl.handle.net/10547/297889
DOI:
10.1145/1840784.1840805
Additional Links:
http://portal.acm.org/citation.cfm?doid=1840784.1840805
Type:
Conference papers, meetings and proceedings
Language:
en
ISBN:
9781450302470
Appears in Collections:
Centre for Research in Distributed Technologies (CREDIT)

Full metadata record

DC FieldValue Language
dc.contributor.authorLiu, Haimingen_GB
dc.contributor.authorMulholland, Paulen_GB
dc.contributor.authorSong, Daweien_GB
dc.contributor.authorUren, Victoriaen_GB
dc.contributor.authorRüger, Stefanen_GB
dc.date.accessioned2013-08-12T08:25:07Z-
dc.date.available2013-08-12T08:25:07Z-
dc.date.issued2010-
dc.identifier.citationLiu, H., Mulholland, P, Song, D., Uren, V. and Rüger, S. (2010) 'Applying information foraging theory to understand user interaction with content-based image retrieval', IIiX '10 Proceedings of the third symposium on Information interaction in context, pp. 135-144en_GB
dc.identifier.isbn9781450302470-
dc.identifier.doi10.1145/1840784.1840805-
dc.identifier.urihttp://hdl.handle.net/10547/297889-
dc.description.abstractThe paper proposes an ISE (Information goal, Search strategy, Evaluation threshold) user classification model based on Information Foraging Theory for understanding user interaction with content-based image retrieval (CBIR). The proposed model is verified by a multiple linear regression analysis based on 50 users' interaction features collected from a task-based user study of interactive CBIR systems. To our best knowledge, this is the first principled user classification model in CBIR verified by a formal and systematic qualitative analysis of extensive user interaction data.en_GB
dc.language.isoenen
dc.publisherACMen_GB
dc.relation.urlhttp://portal.acm.org/citation.cfm?doid=1840784.1840805en_GB
dc.titleApplying information foraging theory to understand user interaction with content-based image retrievalen
dc.typeConference papers, meetings and proceedingsen
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