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Minimally Complete Retrieval in Recommender Systems

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

McSherry, DMG (2008) Minimally Complete Retrieval in Recommender Systems. In: 19th Irish Conference on Artificial Intelligence and Cognitive Science, Cork, Ireland. UNSPECIFIED. 10 pp. [Conference contribution]

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Abstract

Most retrieval algorithms in recommender systems are incomplete in the sense that the existence of a product that satisfies a given subset of the constraints in a user’s query does not guarantee that such a product will be retrieved. Moreover, no existing retrieval algorithm is minimally complete (i.e., always produces a retrieval set of the smallest possible size required for completeness). In this paper, we present an algorithm for minimally complete retrieval called MCR-1 and show how similarity can also be used to inform the retrieval process. We also present theoretical results that enable the maximum possible size of the MCR-1 retrieval set to be determined for a given query, and show empirically that the algorithm tends to produce much smaller retrieval sets than are possible in theory as query size increases.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
ID Code:8889
Deposited By:Dr David McSherry
Deposited On:26 Jan 2010 16:37
Last Modified:26 Jan 2010 16:37

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