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]
Full text not available from this repository.
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
|Deposited By:||Dr David McSherry|
|Deposited On:||26 Jan 2010 16:37|
|Last Modified:||26 Jan 2010 16:37|
Repository Staff Only: item control page