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  • × author_ss:"Humphrey, S.M."
  1. Humphrey, S.M.: Use and management of classification systems for knowledge-based indexing (1992) 0.02 
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    Abstract
    The MedIndEx (Medical Indexing Expert) research project combines artificial intelligence and information retrieval principles and methods to develop and test an interactive knowledge-based prototype for computer-assisted indexing of the MEDLINE database. By encoding the indexing scheme in a knowledge base, and designing a system for indexers to use in a workstation environment, the objective of this project is to facilitate "expert indexing" that is performed at the National Library of Medicine
    Source
    Classification research for knowledge representation and organization. Proc. 5th Int. Study Conf. on Classification Research, Toronto, Canada, 24.-28.6.1991. Ed. by N.J. Williamson u. M. Hudon
  2. Humphrey, S.M.: ¬The MedIndEx prototype for computer assisted MEDLINE database indexing (1993) 0.01 
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    Source
    Indexing, providing access to information: looking back, looking ahead. Proceedings of the 25th Annual Meeting of the American Society of Indexers. Ed.: N.C. Mulvany
  3. Humphrey, S.M.: Knowledge-based systems for indexing (1994) 0.01 
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    Abstract
    Human indexing for information retrieval is intellectually labor intensive. It requires maintaining a system of indexing rules and policies, which in turn require maintaining a controlled indexing vocabulary. These activities are being performed at the National Library of Medicine in support of indexing the MEDLINE database using the MeSH thesaurus. An additional requirement of the conventional indexing operation is maintaining and developing a user interface, known as the Automated Indexing and Management System (AIMS). Describes knowledge-based indexing, based on a unique prototype, called MedIndEx (Medical Indexing Expert)
    Imprint
    Medford, NJ : Learned information
  4. Humphrey, S.M.; Névéol, A.; Browne, A.; Gobeil, J.; Ruch, P.; Darmoni, S.J.: Comparing a rule-based versus statistical system for automatic categorization of MEDLINE documents according to biomedical specialty (2009) 0.00 
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    Abstract
    Automatic document categorization is an important research problem in Information Science and Natural Language Processing. Many applications, including, Word Sense Disambiguation and Information Retrieval in large collections, can benefit from such categorization. This paper focuses on automatic categorization of documents from the biomedical literature into broad discipline-based categories. Two different systems are described and contrasted: CISMeF, which uses rules based on human indexing of the documents by the Medical Subject Headings (MeSH) controlled vocabulary in order to assign metaterms (MTs), and Journal Descriptor Indexing (JDI), based on human categorization of about 4,000 journals and statistical associations between journal descriptors (JDs) and textwords in the documents. We evaluate and compare the performance of these systems against a gold standard of humanly assigned categories for 100 MEDLINE documents, using six measures selected from trec_eval. The results show that for five of the measures performance is comparable, and for one measure JDI is superior. We conclude that these results favor JDI, given the significantly greater intellectual overhead involved in human indexing and maintaining a rule base for mapping MeSH terms to MTs. We also note a JDI method that associates JDs with MeSH indexing rather than textwords, and it may be worthwhile to investigate whether this JDI method (statistical) and CISMeF (rule-based) might be combined and then evaluated showing they are complementary to one another.
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.12, S.2530-2539
  5. Lancaster, F.W.; Ulvila, J.W.; Humphrey, S.M.; Smith, L.C.; Allen, B.; Herner, S.: Evaluation of interactive knowledge-based systems : overview and design for empirical testing (1996) 0.00 
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    Source
    Journal of the American Society for Information Science. 47(1996) no.1, S.57-69
  6. Humphrey, S.M.: Automatic indexing of documents from journal descriptors : a preliminary investigation (1999) 0.00 
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    Source
    Journal of the American Society for Information Science. 50(1999) no.8, S.661-674
  7. Humphrey, S.M.; Rogers, W.J.; Kilicoglu, H.; Demner-Fushman, D.; Rindflesch, T.C.: Word sense disambiguation by selecting the best semantic type based on journal descriptor indexing : preliminary experiment (2006) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.1, S.96-113

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