Abstract
ABSTRACTScholars increasingly use text and data mining (TDM) methods to discover trends and relationships within complex digital data sets. In order to support this development in scholarly communication, librarians and publishers need to be knowledgeable about TDM methods, build partnerships with TDM researchers, and address challenges related to licensing and access to large document sets. The presenters of this NASIG session shared their experiences of supporting TDM as a library subject liaison, acquisitions librarian, and publisher representatives. Audience members discussed issues involving TDM of data from multiple publishers, local hosting of data sets and TDM activity by undergraduate students.
Highlights
As promised by the title of their presentation, the speakers provided a comprehensive overview of text mining and how it impacts and provides opportunities to libraries, library service providers, publishers, and, most importantly, researchers
Of Carnegie Mellon, highlighted examples of text mining projects that use word clouds built from mining large texts, including a class project looking at case documents in the Authors Guild v
Pullman posed the question of how a librarian can stay informed in order to bring these new tools and methods to faculty and student patrons. He remains informed by reviewing faculty curriculum vitae, publications, syllabi, Novak discussed the acquisition factors associated with text mining
Summary
As promised by the title of their presentation, the speakers provided a comprehensive overview of text mining and how it impacts and provides opportunities to libraries, library service providers, publishers, and, most importantly, researchers. Novak of Carnegie Mellon started the program off by defining text mining as “the automated processing of large amounts of structured digital texts” which enables researchers to analyze and interpret massive amounts of textual data, an impossibility using traditional retrieval methods. Of Carnegie Mellon, highlighted examples of text mining projects that use word clouds built from mining large texts, including a class project looking at case documents in the Authors Guild v.
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