Exploration of applying a theory-based user classification model to inform personalised content-based image retrieval system design

2.50
Hdl Handle:
http://hdl.handle.net/10547/622043
Title:
Exploration of applying a theory-based user classification model to inform personalised content-based image retrieval system design
Authors:
Liu, Haiming; Song, Dawei; Mulholland, Paul
Abstract:
To better understand users and create more personalised search experiences, a number of user models have been developed, usually based on different theories or empirical data study. After developing the user models, it is important to effectively utilise them in the design, development and evaluation of search systems to improve users’ overall search experiences. However there is a lack of research has been done on the utilisation of the user models especially theory-based models, because of the challenges on the utilization methodologies when applying the model to different search systems. This paper explores and states how to apply an Information Foraging Theory (IFT) based user classification model called ISE to effectively identify user’s search characteristics and create user groups, based on an empirically-driven methodology for content-based image retrieval (CBIR) systems and how the preferences of different user types inform the personalized design of the CBIR systems.
Affiliation:
University of Bedfordshire; Open University
Citation:
Liu H, Song D, Mulholland P (2016) 'Exploration of applying a theory-based user classification model to inform personalised content-based image retrieval system design', Conference on HCI Korea - Kohan.
Publisher:
ACM
Issue Date:
29-Jan-2016
URI:
http://hdl.handle.net/10547/622043
DOI:
10.17210/hcik.2016.01.61
Additional Links:
http://dl.acm.org/citation.cfm?id=2903636
Type:
Conference papers, meetings and proceedings
Language:
en
Description:
© ACM, 2016. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published at http://dl.acm.org/citation.cfm?id=2903636
ISBN:
9788968487910
Appears in Collections:
Computing

Full metadata record

DC FieldValue Language
dc.contributor.authorLiu, Haimingen
dc.contributor.authorSong, Daweien
dc.contributor.authorMulholland, Paulen
dc.date.accessioned2017-03-02T13:43:10Z-
dc.date.available2017-03-02T13:43:10Z-
dc.date.issued2016-01-29-
dc.identifier.citationLiu H, Song D, Mulholland P (2016) 'Exploration of applying a theory-based user classification model to inform personalised content-based image retrieval system design', Conference on HCI Korea - Kohan.en
dc.identifier.isbn9788968487910-
dc.identifier.doi10.17210/hcik.2016.01.61-
dc.identifier.urihttp://hdl.handle.net/10547/622043-
dc.description© ACM, 2016. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published at http://dl.acm.org/citation.cfm?id=2903636en
dc.description.abstractTo better understand users and create more personalised search experiences, a number of user models have been developed, usually based on different theories or empirical data study. After developing the user models, it is important to effectively utilise them in the design, development and evaluation of search systems to improve users’ overall search experiences. However there is a lack of research has been done on the utilisation of the user models especially theory-based models, because of the challenges on the utilization methodologies when applying the model to different search systems. This paper explores and states how to apply an Information Foraging Theory (IFT) based user classification model called ISE to effectively identify user’s search characteristics and create user groups, based on an empirically-driven methodology for content-based image retrieval (CBIR) systems and how the preferences of different user types inform the personalized design of the CBIR systems.en
dc.language.isoenen
dc.publisherACMen
dc.relation.urlhttp://dl.acm.org/citation.cfm?id=2903636en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectpersonalisationen
dc.subjectpersonalised searchen
dc.subjectISE user classification modelen
dc.subjectIFTen
dc.subjectuser model utilisationen
dc.subjectCBIRen
dc.subjectG440 Human-computer Interactionen
dc.titleExploration of applying a theory-based user classification model to inform personalised content-based image retrieval system designen
dc.typeConference papers, meetings and proceedingsen
dc.contributor.departmentUniversity of Bedfordshireen
dc.contributor.departmentOpen Universityen
dc.date.updated2017-03-02T13:30:11Z-
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