Personal Publication Assistant: Abstract recommendations by a cognitive model

This paper discusses an analysis of how scientists select relevant publications, and an application that can assist scientists in this information selection task. The application, called the Personal Publication Assistant, is based on the assumption that successful information selection is driven by recognizing familiar terms. To adapt itself to a researcher's interests, the system takes into account what words have been used in a particular researcher's abstracts, and when these words have been used. The user model underlying the Personal Publication Assistant is based on a rational analysis of memory, and takes the form of a model of declarative memory as developed for the cognitive architecture ACT-R. We discuss an experiment testing the assumptions of this model and present a user study that validates the implementation of the Personal Publication Assistant. The user study shows that the Personal Publication Assistant can successfully make an initial selection of relevant papers from a large collection of scientific literature.