A Hybrid, Multi-dimensional Recommender for Journal Articles in a Scientific Digital Library
Andre N. Vellino, David Zeber · 2007
A recommender system for scientific scholarly articles that is both hybrid (content and collaborative filtering based) and multi-dimensional (across metadata categories such as subject hierarchies, journal clusters and keyphrases) can improve scientists ’ ability to discover new knowledge from a digital library. Providing users with an interface which enables the filtering of recommendations across these multiple dimensions can simultaneously provide explanations for the recommendations and increase the user’s control over how the recommender behaves. 1