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Supporting webpage revisiting with history data and visualization

Van , Trien Do (2013) Supporting webpage revisiting with history data and visualization. PhD thesis, University of Leeds.

Do_TV_Computing_PhD_2013.pdf - Final eThesis - complete (pdf)
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This research addresses the general topic of “keeping found things found” by investigating difficulties people encounter when revisiting webpages. The overall aim of the research is to design, develop and evaluate a web history tool that addresses these difficulties. An empirical study has been conducted. Participants recorded their web navigation for three months using a Firefox add-on. Each participant then took part in a controlled laboratory experiment, to revisit webpages they had visited neither frequently (on only one day) nor recently (1 week or 1 month ago). Ten underlying causes of failure were discovered. Overall, 61% of the failures occurred when the target page: 1) had originally been accessed via search results; 2) was on a topic a participant often looked at; or 3) was on a known but large website. Based on the findings of the empirical study, a new visualization history tool which supports people in revisiting webpages has been designed and developed as an add-on for Firefox. The tool has two main novel aspects. Firstly, by providing different navigation techniques, it enables users to revisit webpages within their long-term web history. Secondly, the visualization presentation is created based on the user’s navigational paths (even crossing different tabs) rather than the chronology which webpages were visited. Evidence about the benefits of the visualization history tool has been provided through a three month field study. The results showed that such a history tool solved the identified causes of failure and helped participants succeed on 96% of revisiting occasions. They particularly used the tool to revisit webpages which had been visited neither frequently and nor recently. Participants often took only 3 steps to revisit a webpage. Overall, they were satisfied with the tool and rated it 4.1/5.0, and 84% of them wanted to keep using the tool after the evaluation.

Item Type: Thesis (PhD)
ISBN: 978-0-85731-442-0
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Computing (Leeds)
Identification Number/EthosID: uk.bl.ethos.589252
Depositing User: Repository Administrator
Date Deposited: 17 Dec 2013 13:20
Last Modified: 25 Nov 2015 13:41
URI: http://etheses.whiterose.ac.uk/id/eprint/4883

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