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

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

Open University Milton Keynes
,
Robert Gordon University
,
University of Sheffield

Research Output:

Chapter in Book/Report/Conference proceeding

Conference contribution

Peer-review

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.

Publication Information

Output type

Research Output:

Chapter in Book/Report/Conference proceeding

Conference contribution

Peer-review

Original language

English

Publication milestones

Published - 01/01/2010

Publication status

Published - 01/01/2010

Publisher

Association for Computing Machinery, United States

ISBN (Print)

9781450302470

ISBN (Electronic)

9781450302470

Publication IDs

handle.net: 10547/297889
Scopus: 77957961245

Host publication title

nan

Access to documents

10.1145/1840784.1840805

Handle.net

Persistent link

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citations

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Related Event

Title

3rd Information Interaction in Context Symposium

Description

3rd Information Interaction in Context Symposium

Event type

Conference

Date

01/01/2010