HelpfulMed: Intelligent Searching for Medical Information over the Internet

Persistent Link:
http://hdl.handle.net/10150/105202
Title:
HelpfulMed: Intelligent Searching for Medical Information over the Internet
Author:
Chen, Hsinchun; Lally, Ann M.; Zhu, Bin; Chau, Michael
Citation:
HelpfulMed: Intelligent Searching for Medical Information over the Internet 2003-05, 54(7):683-694 Journal of the American Society for Information Science & Technology
Publisher:
Wiley Periodicals, Inc
Journal:
Journal of the American Society for Information Science & Technology
Issue Date:
May-2003
Description:
Artificial Intelligence Lab, Department of MIS, University of Arizona
URI:
http://hdl.handle.net/10150/105202
Submitted date:
2004-08-16
Abstract:
Medical professionals and researchers need information from reputable sources to accomplish their work. Unfortunately, the Web has a large number of documents that are irrelevant to their work, even those documents that purport to be â medically-related.â This paper describes an architecture designed to integrate advanced searching and indexing algorithms, an automatic thesaurus, or â concept space,â and Kohonen-based Self-Organizing Map (SOM) technologies to provide searchers with finegrained results. Initial results indicate that these systems provide complementary retrieval functionalities. HelpfulMed not only allows users to search Web pages and other online databases, but also allows them to build searches through the use of an automatic thesaurus and browse a graphical display of medical-related topics. Evaluation results for each of the different components are included. Our spidering algorithm outperformed both breadth-first search and PageRank spiders on a test collection of 100,000 Web pages. The automatically generated thesaurus performed as well as both MeSH and UMLSâ systems which require human mediation for currency. Lastly, a variant of the Kohonen SOM was comparable to MeSH terms in perceived cluster precision and significantly better at perceived cluster recall.
Type:
Journal Article (Paginated)
Language:
en
Keywords:
Web Mining; Medical Libraries
Local subject classification:
National Science Digital Library; NSDL; Artificial intelligence lab; AI lab; HelpfulMed

Full metadata record

DC FieldValue Language
dc.contributor.authorChen, Hsinchunen_US
dc.contributor.authorLally, Ann M.en_US
dc.contributor.authorZhu, Binen_US
dc.contributor.authorChau, Michaelen_US
dc.date.accessioned2004-08-16T00:00:01Z-
dc.date.available2010-06-18T23:21:30Z-
dc.date.issued2003-05en_US
dc.date.submitted2004-08-16en_US
dc.identifier.citationHelpfulMed: Intelligent Searching for Medical Information over the Internet 2003-05, 54(7):683-694 Journal of the American Society for Information Science & Technologyen_US
dc.identifier.urihttp://hdl.handle.net/10150/105202-
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractMedical professionals and researchers need information from reputable sources to accomplish their work. Unfortunately, the Web has a large number of documents that are irrelevant to their work, even those documents that purport to be â medically-related.â This paper describes an architecture designed to integrate advanced searching and indexing algorithms, an automatic thesaurus, or â concept space,â and Kohonen-based Self-Organizing Map (SOM) technologies to provide searchers with finegrained results. Initial results indicate that these systems provide complementary retrieval functionalities. HelpfulMed not only allows users to search Web pages and other online databases, but also allows them to build searches through the use of an automatic thesaurus and browse a graphical display of medical-related topics. Evaluation results for each of the different components are included. Our spidering algorithm outperformed both breadth-first search and PageRank spiders on a test collection of 100,000 Web pages. The automatically generated thesaurus performed as well as both MeSH and UMLSâ systems which require human mediation for currency. Lastly, a variant of the Kohonen SOM was comparable to MeSH terms in perceived cluster precision and significantly better at perceived cluster recall.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherWiley Periodicals, Incen_US
dc.subjectWeb Miningen_US
dc.subjectMedical Librariesen_US
dc.subject.otherNational Science Digital Libraryen_US
dc.subject.otherNSDLen_US
dc.subject.otherArtificial intelligence laben_US
dc.subject.otherAI laben_US
dc.subject.otherHelpfulMeden_US
dc.titleHelpfulMed: Intelligent Searching for Medical Information over the Interneten_US
dc.typeJournal Article (Paginated)en_US
dc.identifier.journalJournal of the American Society for Information Science & Technologyen_US
All Items in UA Campus Repository are protected by copyright, with all rights reserved, unless otherwise indicated.