Recommender Systems for Configuration Knowledge Engineering
Information Retrieval
2021-02-17 v1 Artificial Intelligence
Abstract
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.
Cite
@article{arxiv.2102.08113,
title = {Recommender Systems for Configuration Knowledge Engineering},
author = {Alexander Felfernig and Stefan Reiterer and Martin Stettinger and Florian Reinfrank and Michael Jeran and Gerald Ninaus},
journal= {arXiv preprint arXiv:2102.08113},
year = {2021}
}
Comments
A. Felfernig S, Reiterer, M. Stettinger, F. Reinfrank, M. Jeran, and G. Ninaus. Recommender Systems for Configuration Knowledge Engineering, Workshop on Configuration, Vienna, Austria, pp. 51-54, ISBN: 979-10-91526-02-9, 2013