Recommender Systems for Problem Solving Environments

Naren Ramakrishnan, Elias N. Houstis, and John R. Rice

Traditionally, recommender systems have been studied in domains that focus on harnessing distributed information resources, collaborative filtering, information aggregation, social schemes for decision making and user interfaces. In this paper, we present recommender systems in a different context -- primarily as systems that select (scientific) software appropriate to a user’s needs. This application is motivated by the wide acceptance of problem solving environments (PSEs) which are high level environments for doing computational science. We give an overview of the domain, argue the need for recommender systems and describe our work in this area. The research issues in this discipline are also highlighted.


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