A theory of diagnosis from first principles
Artificial Intelligence
Artificial Intelligence
Using crude probability estimates to guide diagnosis
Artificial Intelligence
Characterizing diagnoses and systems
Artificial Intelligence
Consistency-based diagnosis of configuration knowledge bases
Artificial Intelligence
Query relaxation using malleable schemas
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Debugging Incoherent Terminologies
Journal of Automated Reasoning
QUICKXPLAIN: preferred explanations and relaxations for over-constrained problems
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Representative explanations for over-constrained problems
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Plausible repairs for inconsistent requirements
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
FastXplain: conflict detection for constraint-based recommendation problems
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
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Knowledge-based recommender systems support users in finding interesting products from large and potentially complex product assortments. In such systems users continuously refine their specifications which the product has to satisfy. If the specifications are too narrow no product can be retrieved from the product assortment. Instead of just notifying the customer that no product could be found we introduce an approach called ReAction to support customers with minimal repair adaptations. In this paper we give a detailed explanation of our algorithm. Besides that we present the results of a detailed empirical evaluation focussing on the quality as well as on the runtime performance. The work presented is relevant for designers and developers of database systems as well as knowledge-based recommender systems interested in (i) identifying relaxations for database queries, (ii) applying and dealing with user utilities, and (iii) improving the system usability through suggesting minimal repair adaptations for inconsistent queries.