SciFinder Scholar 2006: an empirical analysis of research topic query processing.

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  • Author(s): Wagner AB;Wagner AB
  • Source:
    Journal of chemical information and modeling [J Chem Inf Model] 2006 Mar-Apr; Vol. 46 (2), pp. 767-74.
  • Publication Type:
    Journal Article
  • Language:
    English
  • Additional Information
    • Source:
      Publisher: American Chemical Society Country of Publication: United States NLM ID: 101230060 Publication Model: Print Cited Medium: Print ISSN: 1549-9596 (Print) Linking ISSN: 15499596 NLM ISO Abbreviation: J Chem Inf Model Subsets: MEDLINE
    • Publication Information:
      Original Publication: Washington, D.C. : American Chemical Society, c2005-
    • Subject Terms:
      Algorithms* ; Databases as Topic* ; Natural Language Processing* ; Software*; Information Services/*trends; Information Services/statistics & numerical data ; Molecular Structure ; Research Design ; User-Computer Interface
    • Abstract:
      Topical 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.
    • Publication Date:
      Date Created: 20060328 Date Completed: 20060908 Latest Revision: 20071115
    • Publication Date:
      20240829
    • Accession Number:
      10.1021/ci050481b
    • Accession Number:
      16563008