Applying Information Foraging Theory to understand user interaction with content-based image retrieval

Haiming Liu; Paul Mulholland; Dawei Song; Victoria Uren; Stefan Rüger

doi:10.1145/1840784.1840805

Applying Information Foraging Theory to understand user interaction with content-based image retrieval

Haiming Liu^*, Paul Mulholland, Dawei Song, Victoria Uren, Stefan Rüger

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

22 Citations (Scopus)

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.

Original language	English
Title of host publication	IIiX 2010 - Proceedings of the 2010 Information Interaction in Context Symposium
Pages	135-144
Number of pages	10
DOIs	https://doi.org/10.1145/1840784.1840805
Publication status	Published - 2010
Externally published	Yes
Event	3rd Information Interaction in Context Symposium, IIiX'10 - New Brunswick, NJ, United States Duration: 18 Aug 2010 → 21 Aug 2010

Publication series

Name	IIiX 2010 - Proceedings of the 2010 Information Interaction in Context Symposium

Conference

Conference	3rd Information Interaction in Context Symposium, IIiX'10
Country/Territory	United States
City	New Brunswick, NJ
Period	18/08/10 → 21/08/10

Keywords

Content-based image retrieval
Exploratory Search
Information foraging theory
User interaction
User modelling

Access to Document

10.1145/1840784.1840805

Cite this

Liu, H., Mulholland, P., Song, D., Uren, V., & Rüger, S. (2010). Applying Information Foraging Theory to understand user interaction with content-based image retrieval. In IIiX 2010 - Proceedings of the 2010 Information Interaction in Context Symposium (pp. 135-144). (IIiX 2010 - Proceedings of the 2010 Information Interaction in Context Symposium). https://doi.org/10.1145/1840784.1840805

@inproceedings{bb95f54d38eb4d879b8f0dc4640012af,

title = "Applying Information Foraging Theory to understand user interaction with content-based image retrieval",

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.",

keywords = "Content-based image retrieval, Exploratory Search, Information foraging theory, User interaction, User modelling",

author = "Haiming Liu and Paul Mulholland and Dawei Song and Victoria Uren and Stefan R{\"u}ger",

year = "2010",

doi = "10.1145/1840784.1840805",

language = "English",

isbn = "9781450302470",

series = "IIiX 2010 - Proceedings of the 2010 Information Interaction in Context Symposium",

pages = "135--144",

booktitle = "IIiX 2010 - Proceedings of the 2010 Information Interaction in Context Symposium",

note = "3rd Information Interaction in Context Symposium, IIiX'10 ; Conference date: 18-08-2010 Through 21-08-2010",

}

Liu, H, Mulholland, P, Song, D, Uren, V & Rüger, S 2010, Applying Information Foraging Theory to understand user interaction with content-based image retrieval. in IIiX 2010 - Proceedings of the 2010 Information Interaction in Context Symposium. IIiX 2010 - Proceedings of the 2010 Information Interaction in Context Symposium, pp. 135-144, 3rd Information Interaction in Context Symposium, IIiX'10, New Brunswick, NJ, United States, 18/08/10. https://doi.org/10.1145/1840784.1840805

Applying Information Foraging Theory to understand user interaction with content-based image retrieval. / Liu, Haiming; Mulholland, Paul; Song, Dawei et al.
IIiX 2010 - Proceedings of the 2010 Information Interaction in Context Symposium. 2010. p. 135-144 (IIiX 2010 - Proceedings of the 2010 Information Interaction in Context Symposium).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Applying Information Foraging Theory to understand user interaction with content-based image retrieval

AU - Liu, Haiming

AU - Mulholland, Paul

AU - Song, Dawei

AU - Uren, Victoria

AU - Rüger, Stefan

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

KW - Content-based image retrieval

KW - Exploratory Search

KW - Information foraging theory

KW - User interaction

KW - User modelling

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U2 - 10.1145/1840784.1840805

DO - 10.1145/1840784.1840805

M3 - Conference contribution

AN - SCOPUS:77957961245

SN - 9781450302470

T3 - IIiX 2010 - Proceedings of the 2010 Information Interaction in Context Symposium

SP - 135

EP - 144

BT - IIiX 2010 - Proceedings of the 2010 Information Interaction in Context Symposium

T2 - 3rd Information Interaction in Context Symposium, IIiX'10

Y2 - 18 August 2010 through 21 August 2010

ER -

Applying Information Foraging Theory to understand user interaction with content-based image retrieval

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Keywords

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