In this age of Big Data, the “recommender system” — a la Amazon.com — has emerged as a way of prioritizing descriptive information based on social behavior. Shoppers of Amazon are familiar with the words, “Customers who bought this item also bought,” followed by images of suggested books. But how could university libraries provide tools that will help patrons access the full depth of their comprehensive content? Taking on that investigation is a team composed of Principal Investigator Harriett Green and Kirk Hess of the University of Illinois at Urbana-Champaign (UIUC) Library, along with Richard Hislop of the UIUC Department of Economics. The Nautilus supercomputer, housed at Oak Ridge National Laboratory and managed by the National Institute for Computational Sciences (NICS), provided high-performance computing support to the project, which entailed data mining involving the 14 million items in the UIUC Library. To read further, please visit http://www.nics.tennessee.edu/library-collection-research.