Others also use: A robust recommender system for scientific libraries

Abstract

Scientific digital library systems are a very promising application area for value-added expert advice services. Such systems could significantly reduce the search and evaluation costs of information products for students and scientists. This holds for pure digital libraries as well as for traditional scientific libraries with online public access catalogs (OPAC). In this contribution we first outline different types of recommendation services for scientific libraries and their general integration strategies. Then we focus on a recommender system based on log file analysis that is fully operational within the legacy library system of the Universität Karlsruhe (TH) since June 2002. Its underlying mathematical model, the implementation within the OPAC, as well as the first user evaluation is presented. © Springer-Verlag 2003.