Artificial Intelligence Lab, Department of MIS, University of Arizona / 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.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/106024 |
| Date | January 2003 |
| Creators | Chen, Hsinchun, Fan, Haiyan, Chau, Michael, Zeng, Daniel |
| Publisher | Elsevier |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Journal Article (Paginated) |
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