by Barbara Weir
We’ve become accustomed to seeing recommendations for new and interesting books from Amazon, films from Netflix, and friends from Facebook, but now students and faculty can get recommendations about articles too. The library has subscribed to a service called bX Recommender which uses log files contributed by member libraries in order to provide patrons with information about articles which may be relevant to their research.
In the example below, a patron is interested in an article about self-regulated learning. The bX recommender has found three articles which may also be relevant, based on use by other patrons. This information is presented in the FindIt menu.
The bX recommender service is provided by the Ex Libris Corporation and is based on research conducted by Johan Bollen and Herbert Van de Sompel at the Los Alamos National Laboratory. The recommendations are generated from data originating from tens of millions of discovery sessions at hundreds of institutions around the world. Ex Libris harvests this data, mines it, and analyzes it to produce useful recommendations for scholars.