Faculty and Staff Research and Scholarship - Library and Information Science

 

Our exceptional faculty includes nationally recognized, award-winning, innovative teachers and researchers, who combine strong teaching skills with specialty expertise. They are regularly included on the university's lists of "teachers rated excellent by their students," and are active researchers. Find out more about iSchool faculty.

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  • Jackson, Sally A.; Schneider, Jodi (2016-07-09)
    Health controversies are infused with products of expert reasoning, often interpreted by non-experts. To understand these controversies, we must pay closer attention both to the field-dependent devices that characterize ...

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    application/pdfPDF (520kB)
  • Kehoe, Adam K.; Torvik, Vetle I. (ACM, 2016-06)
    We describe a classifier-enhanced nearest neighbor approach to assigning Medical Subject Headings (MeSH) to unlabeled documents using a combination of abstract similarities and direct citations to labeled MEDLINE records. ...

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    application/pdfPDF (303kB)
  • Kyrillidou, Martha; Cook, Colleen; Lippincott, Sarah (Emerald Publishing, 2016-01-01)
    Purpose: To describe a model of digital library work that surfaced through the ARL Profiles 2010 and resonates current work underway by the large scale digital library projects like DPLA, SHARE, Hathitrust, Academic ...

    application/vnd.openxmlformats-officedocument.wordprocessingml.document

    application/vnd.openxmlformats-officedocument.wordprocessingml.documentMicrosoft Word 2007 (59kB)
  • Martin Wolske (2016-03-24)

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    application/pdfPDF (2MB)
  • Organisciak, Peter (2016-03)
    A popular form of term weighting in texts is to use TF*IDF, which takes a text's term frequencies and weighs them by a measure derived from document frequency called Inverse Document Frequency (IDF). This dataset provides ...

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    text/csvCSV file (37MB)

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