---
title: "Plausible Repairs for Inconsistent Requirements"
authors:
  - "Alexander Felfernig"
  - "Gerhard Friedrich"
  - "Monika Schubert"
  - "Monika Mandl"
  - "Markus Mairitsch"
  - "Erich Teppan"
doi: ""
url: "https://ijcai.org/proceedings/2009/136"
pdf: "https://ijcai.org/proceedings/2009/0136.pdf"
venue: "Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence"
year: 2009
pages: ""
track: ""
keywords:
---

# Plausible Repairs for Inconsistent Requirements

Alexander Felfernig, Gerhard Friedrich, Monika Schubert, Monika Mandl, Markus Mairitsch, Erich Teppan

*Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence*.

## 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.