Recommender systems for scientific digital libraries that have been the subject of experiments in recent years have used corpora that are primarily in the field of computer science. However, designing an effective recommender system for journal articles in a broader Scientific, Technical and Medical (STM) digital library poses special challenges and presents unique opportunities.
This talk describes a recommender system for scientific scholarly articles that is both hybrid (content and collaborative filtering based) and multi-dimensional (across different rating criteria.) Our hypothesis is that such a design for a recommendation engine can improve scientists’ ability to discover new knowledge from a digital library provided that an interface to these recommendations can simultaneously offer explanations for the recommendations and increase the user’s control over how the recommender behaves.
The talk will be webcasted: mms://mediasrv.lorit.ca/presentation using Microsoft-only technology.
It says that the talk will be in French.