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Literature-based discovery by lexical statistics

dc.contributor.authorLindsay, Robert K.en_US
dc.contributor.authorGordon, Michael D.en_US
dc.date.accessioned2006-04-19T13:25:20Z
dc.date.available2006-04-19T13:25:20Z
dc.date.issued1999en_US
dc.identifier.citationLindsay, Robert K.; Gordon, Michael D. (1999)."Literature-based discovery by lexical statistics." Journal of the American Society for Information Science 50(7): 574-587. <http://hdl.handle.net/2027.42/34257>en_US
dc.identifier.issn0002-8231en_US
dc.identifier.issn1097-4571en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/34257
dc.description.abstractWe report experiments that use lexical statistics, such as word frequency counts, to discover hidden connections in the medical literature. Hidden connections are those that are unlikely to be found by examination of bibliographic citations or the use of standard indexing methods and yet establish a relationship between topics that might profitably be explored by scientific research. Our experiments were conducted with the MEDLINE medical literature database and follow and extend the work of Swanson.en_US
dc.format.extent100537 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherJohn Wiley & Sons, Inc.en_US
dc.subject.otherComputer Scienceen_US
dc.titleLiterature-based discovery by lexical statisticsen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbtoplevelHumanitiesen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumMental Health Research Institute, University of Michigan Medical School, 205 Zina Pitcher Place, Ann Arbor, MI 48109en_US
dc.contributor.affiliationumUniversity of Michigan Business School, 701 Tappan Street, Ann Arbor, MI 48109en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/34257/1/3_ftp.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1002/(SICI)1097-4571(1999)50:7<574::AID-ASI3>3.0.CO;2-Qen_US
dc.identifier.sourceJournal of the American Society for Information Scienceen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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