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    Testing a Cancer Meta Spider

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    Author
    Chen, Hsinchun
    Fan, Haiyan
    Chau, Michael
    Zeng, Daniel
    Issue Date
    2003
    Submitted date
    2004-08-16
    Keywords
    Human Computer Interaction
    Database Searching Instructions
    Local subject classification
    National Science Digital Library
    NSDL
    Artificial intelligence lab
    AI lab
    Cancer spider
    
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    Citation
    Testing a Cancer Meta Spider 2003, 59(1):755-776 International Journal of Human-computer Studies
    Publisher
    Elsevier
    Journal
    International Journal of Human-computer Studies
    Description
    Artificial Intelligence Lab, Department of MIS, University of Arizona
    URI
    http://hdl.handle.net/10150/106024
    Abstract
    As in many other applications, the rapid proliferation and unrestricted Web-based publishing of health-related content have made finding pertinent and useful healthcare information increasingly difficult. Although the development of healthcare information retrieval systems such as medical search engines and peer-reviewed medical Web directories has helped alleviate this information and cognitive overload problem, the effectiveness of these systems has been limited by low search precision, poor presentation of search results, and the required user search effort. To address these challenges, we have developed a domain-specific meta-search tool called Cancer Spider. By leveraging post-retrieval document clustering techniques, this system aids users in querying multiple medical data sources to gain an overview of the retrieved documents and locating answers of high quality to a wide spectrum of health questions. The system presents the retrieved documents to users in two different views: (1) Web pages organized by a list of key phrases, and (2) Web pages clustered into regions discussing different topics on a two-dimensional map (self-organizing map). In this paper, we present the major components of the Cancer Spider system and a user evaluation study designed to evaluate the effectiveness and efficiency of our approach. Initial results comparing Cancer Spider with NLM Gateway, a premium medical search site, have shown that they achieved comparable performances measured by precision, recall, and F-measure. Cancer Spider required less user searching time, fewer documents that need to be browsed, and less user effort.
    Type
    Journal Article (Paginated)
    Language
    en
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