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Artificial Intelligence Review

, Volume 24, Issue 3–4, pp 319–338 | Cite as

Retrieval Failure and Recovery in Recommender Systems

  • David McsherryEmail author
Article

Abstract

In case-based reasoning (CBR) approaches to product recommendation, descriptions of the available products are stored in a case library and retrieved in response to a query representing the user’s requirements. We present an approach to recovery from the retrieval failures that often occur when the user’s requirements are treated as constraints that must be satisfied. Failure to retrieve a matching case triggers a recovery process in which the user is invited to select from a recovery set of relaxations (or sub-queries) of her query that are guaranteed to succeed. The suggested relaxations are ranked according to a simple measure of recovery cost defined in terms of the importance weights assigned to the query attributes. The recovery set for an unsuccessful query also serves as a guide to continued exploration of the product space when none of the cases initially recommended by the system is acceptable to the user

Keywords

case-based reasoning recommender systems retrieval failure query relaxation 

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Copyright information

© Springer 2005

Authors and Affiliations

  1. 1.School of Computing and Information EngineeringUniversity of UlsterColeraineUK

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