Recommender Systems for Configuration Knowledge Engineering

Felfernig, Alexander, Reiterer, Stefan, Stettinger, Martin, Reinfrank, Florian, Jeran, Michael, Ninaus, Gerald

arXiv.org Artificial Intelligence 

The knowledge engineering bottleneck is still a major challenge in configurator projects. In this paper we show how recommender systems can support knowledge base development and maintenance processes. We discuss a couple of scenarios for the application of recommender systems in knowledge engineering and report the results of empirical studies which show the importance of user-centered configuration knowledge organization.

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