Case-based reasoning as a prediction strategy for hybrid recommender systems

van Setten, M. and Veenstra, M. and Nijholt, A. and van Dijk, E.M.A.G. (2004) Case-based reasoning as a prediction strategy for hybrid recommender systems. In: Second International Atlantic Web Intelligence Conference (AWIC 2004), Cancun, Mexico, 16-19 May 2004, Cancun, Mexico.

PDF
Restricted to UT campus only: Request a copy
334Kb

Abstract:	Hybrid recommender systems are capable of providing better rec-ommendations than non-hybrid ones. Our approach to hybrid recommenders is the use of prediction strategies that determine which prediction technique(s) should be used at the moment an actual prediction is required. In this paper, we determine whether case-based reasoning can provide more accurate prediction strategies than rule-based predictions strategies created manually by experts. Experiments show that case-based reasoning can indeed be used to create pre-diction strategies; it can even increase the accuracy of the recommender in sys-tems where the accuracy of the used prediction techniques is highly spread.
Item Type:	Conference or Workshop Item
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Human Media Interaction (HMI)
Link to this item:	http://purl.utwente.nl/publications/63387
Official URL:	http://www.springerlink.com/content/w6ytv56dnyfgr07j
Export this item as:	BibTeX EndNote HTML Citation Reference Manager

Show download statistics for this publication

Repository Staff Only: item control page