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: each of our full-time faculty members has served as principal investigator for at least one grant-funded project in the last two years. Find out more about GSLIS faculty.
(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. ...
(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.documentMicrosoft Word 2007 (59kB)
(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 ...
text/csvCSV file (37MB)
(2016-03)Corpus-level term statistics are valuable for numerous text analysis activities, such as term weighting or probability distribution smoothing. In instances where there is an insufficient corpus to calculate such statistics, ...
text/csvCSV file (39MB)