KUKU

KU ScholarWorks

  • myKU
  • Email
  • Enroll & Pay
  • KU Directory
    • Login
    View Item 
    •   KU ScholarWorks
    • Dissertations and Theses
    • Dissertations
    • View Item
    •   KU ScholarWorks
    • Dissertations and Theses
    • Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    HealthTrust: Assessing the Trustworthiness of Healthcare Information on the Internet

    Thumbnail
    View/Open
    Park_ku_0099D_13091_DATA_1.pdf (1.789Mb)
    Issue Date
    2013-12-31
    Author
    Park, Meeyoung
    Publisher
    University of Kansas
    Format
    120 pages
    Type
    Dissertation
    Degree Level
    Ph.D.
    Discipline
    Electrical Engineering & Computer Science
    Rights
    This item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author.
    Metadata
    Show full item record
    Abstract
    As well recognized, healthcare information is growing exponentially and is made more available to public. Frequent users such as medical professionals and patients are highly dependent on the web sources to get the appropriate information promptly. However, the trustworthiness of the information on the web is always questionable due to the fast and augmentative properties of the Internet. Most search engines provide relevant pages to given keywords, but the results might contain some unreliable or biased information. Consequently, a significant challenge associated with the information explosion is to ensure effective use of information. One way to improve the search results is by accurately identifying more trustworthy data. Surprisingly, although trustworthiness of sources is essential for a great number of daily users, not much work has been done for healthcare information sources by far. In this dissertation, I am proposing a new system named HealthTrust, which automatically assesses the trustworthiness of healthcare information over the Internet. In the first phase, an unsupervised clustering using graph topology, on our collection of data is employed. The goal is to identify a relatively larger and reliable set of trusted websites as a seed set without much human efforts. After that, a new ranking algorithm for structure-based assessment is adopted. The basic hypothesis is that trustworthy pages are more likely to link to trustworthy pages. In this way, the original set of positive and negative seeds will propagate over the Web graph. With the credibility-based discriminators, the global scoring is biased towards trusted websites and away from untrusted websites. Next, in the second phase, the content consistency between general healthcare-related webpages and trusted sites is evaluated using information retrieval techniques to evaluate the content-semantics of the webpage with respect to the medical topics. In addition, graph modeling is employed to generate contents-based ranking for each page based on the sentences in the seed pages. Finally, in order to integrate the two components, an iterative approach that integrates the credibility assessments from structure-based and content-based methods to give a final verdict - a HealthTrust score for each webpage is exploited. I demonstrated the first attempt to integrate structure-based and content-based approaches to automatically evaluate the credibility of online healthcare information through HealthTrust and make fundamental contributions to both information retrieval and healthcare informatics communities.
    URI
    http://hdl.handle.net/1808/14202
    Collections
    • Engineering Dissertations and Theses [1055]
    • Dissertations [4472]

    Items in KU ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.


    We want to hear from you! Please share your stories about how Open Access to this item benefits YOU.


    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

    Browse

    All of KU ScholarWorksCommunities & CollectionsThis Collection

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

    The University of Kansas
      Contact KU ScholarWorks
    Lawrence, KS | Maps
     
    • Academics
    • Admission
    • Alumni
    • Athletics
    • Campuses
    • Giving
    • Jobs

    The University of Kansas prohibits discrimination on the basis of race, color, ethnicity, religion, sex, national origin, age, ancestry, disability, status as a veteran, sexual orientation, marital status, parental status, gender identity, gender expression and genetic information in the University’s programs and activities. The following person has been designated to handle inquiries regarding the non-discrimination policies: Director of the Office of Institutional Opportunity and Access, IOA@ku.edu, 1246 W. Campus Road, Room 153A, Lawrence, KS, 66045, (785)864-6414, 711 TTY.

     Contact KU
    Lawrence, KS | Maps