Prior developments

Appendix 1 of the MOSAIC project report ( mosaic.html) introduces a number of seminal project and service developments, including
  • California Digital Library - The Melvyl Recommender Project team explored two methods of generating recommendations. The first method used circulation data to determine linkages between items ("patrons who checked this out also checked out..."). A second, content- based, strategy used terms from the bibliographic records to develop queries for similar items ("more like this..."). The project showed strong evidence that library users are interested in receiving recommendations to support both academic and personal information needs. See
  • MESUR - MESUR stands for MEtrics from Scholarly Usage of Resources. The MESUR database contains 1 billion usage events obtained from 6 significant publishers, 4 large institutional consortia and 4 significant aggregators. MESUR produces large-scale, longitudinal maps of the scholarly community and a survey of more than 60 different metrics of scholarly impact. See
  • Ex Libris bX - The bX service is the result of research into scholarly recommender systems conducted by the bX team and leading researchers Johan Bollen and Herbert Van de Sompel who were responsible for the MESUR project. Based on data captured through a large- scale aggregation of link-resolver usage logs, bX is an extension of the OpenURL framework. See
  • BibTip - This recommender system is based on statistical evaluation of the usage data. All the data stored and processed are anonymous. See
  • The University of Minnesota Libraries - The University of Minnesota Libraries have created a 'MyLibrary' portal, with databases and e-journals targeted to users, based on their affiliations. For more on affinity strings see