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Plausible Repairs for Inconsistent Requirements
| Citations: | 18 - 9 self |
BibTeX
@MISC{Felfernig_plausiblerepairs,
author = {Alexander Felfernig and Gerhard Friedrich and Monika Schubert and Monika Mandl and Markus Mairitsch and Erich Teppan},
title = {Plausible Repairs for Inconsistent Requirements },
year = {}
}
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Abstract
Knowledge-based recommenders support users in the identification of interesting items from large and potentially complex assortments. In cases where no recommendation could be found for a given set of requirements, such systems propose explanations that indicate minimal sets of faulty requirements. Unfortunately, such explanations are not personalized and do not include repair proposals which triggers a low degree of satisfaction and frequent cancellations of recommendation sessions. In this paper we present a personalized repair approach that integrates the calculation of explanations with collaborative problem solving techniques. In order to demonstrate the applicability of our approach, we present the results of an empirical study that show significant improvements in the accuracy of predictions for interesting repairs.
Keyphrases
inconsistent requirement plausible repair significant improvement personalized repair approach minimal set frequent cancellation complex assortment low degree collaborative problem empirical study recommendation session repair proposal faulty requirement knowledge-based recommenders support user
