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Lin, Yi-Ling (2013) ENHANCING IMAGE FINDABILITY THROUGH A DUAL-PERSPECTIVE NAVIGATION FRAMEWORK. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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This dissertation focuses on investigating whether users will locate desired images more efficiently and effectively when they are provided with information descriptors from both experts and the general public. This study develops a way to support image finding through a human-computer interface by providing subject headings and social tags about the image collection and preserving the information scent (Pirolli, 2007) during the image search experience.
In order to improve search performance most proposed solutions integrating experts’ annotations and social tags focus on how to utilize controlled vocabularies to structure folksonomies which are taxonomies created by multiple users (Peters, 2009). However, these solutions merely map terms from one domain into the other without considering the inherent differences between the two. In addition, many websites reflect the benefits of using both descriptors by applying a multiple interface approach (McGrenere, Baecker, & Booth, 2002), but this type of navigational support only allows users to access one information source at a time. By contrast, this study is to develop an approach to integrate these two features to facilitate finding resources without changing their nature or forcing users to choose one means or the other.
Driven by the concept of information scent, the main contribution of this dissertation is to conduct an experiment to explore whether the images can be found more efficiently and effectively when multiple access routes with two information descriptors are provided to users in the dual-perspective navigation framework. This framework has proven to be more effective and efficient than the subject heading-only and tag-only interfaces for exploratory tasks in this study. This finding can assist interface designers who struggle with determining what information is best to help users and facilitate the searching tasks. Although this study explicitly focuses on image search, the result may be applicable to wide variety of other domains. The lack of textual content in image systems makes them particularly hard to locate using traditional search methods. While the role of professionals in describing items in a collection of images, the role of the crowd in assigning social tags augments this professional effort in a cost effective manner.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Lin, Yi-Lingyil54@pitt.eduYIL54
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairHe, Daqingdah44@pitt.eduDAH44
Committee CoChairBrusilovsky, Peterpeterb@pitt.eduPETERB
Committee MemberFarzan, Rostarfarzan@pitt.eduRFARZAN
Committee MemberSpring, Michael Bspring@pitt.eduSPRING
Committee MemberAroyo,
Date: 11 December 2013
Date Type: Publication
Defense Date: 25 July 2013
Approval Date: 11 December 2013
Submission Date: 3 December 2013
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 176
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: image findability, subject heading, social tags, exploratory search, aboutness, information scent
Date Deposited: 11 Dec 2013 15:09
Last Modified: 15 Nov 2016 14:16


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