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dc.contributor.authorWagner, A. Ben
dc.date.accessioned2012-12-12T19:19:20Z
dc.date.available2012-12-12T19:19:20Z
dc.date.issued2006-03
dc.identifier.citationWagner, A. Ben. 2006. “SciFinder Scholar 2006: An Empirical Analysis of Research Topic Query Processing.” Journal of Chemical Information and Modeling 46(2): 767-774. http://pubs.acs.org/doi/abs/10.1021/ci050481ben_US
dc.identifier.issn1549-960X (electronic)
dc.identifier.urihttp://hdl.handle.net/10477/12891
dc.descriptionThis is the publisher's pdf version of the final article published as: Wagner, A. Ben. 2006. “SciFinder Scholar 2006: An Empirical Analysis of Research Topic Query Processing.” Journal of Chemical Information and Modeling 46(2): 767-774. http://pubs.acs.org/doi/abs/10.1021/ci050481b. Copyright © 2006 American Chemical Society. Article was made open access at the time of publication by special request of the journal editor.
dc.description.abstractTopical search queries in SciFinder Scholar are processed through an extensive set of natural language processing algorithms that greatly enhance the relevance and comprehensiveness of the search results. Little detailed documentation on these algorithms has been published. However, a careful examination of the highlighted hit terms coupled with a comparison of results from small variations in query language reveal much additional, useful information about these algorithms. An understanding of how these algorithms work can lead to better search results and explain many unexpected results, including differing hit counts for singular versus plural query words and phrases.
dc.language.isoen_USen_US
dc.publisherAmerican Chemical Society
dc.subjectchemical information retrieval
dc.subjectChemical Abstracts Service
dc.subjectSciFinder
dc.subjectsearch strategies
dc.subjecttopical searching
dc.subjectnatural language queries
dc.subjectalgorithms
dc.titleSciFinder Scholar 2006: An Empirical Analysis of Research Topic Query Processingen_US
dc.typeArticleen_US


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