Hybrid recommender systems with case-based components

Abstract

Hybrid recommender systems combine recommendation components of different types to achieve improved performance. Many such hybrids have been built but recent studies show that hybrids using case-based recommendation are rare. This paper shows how a range of different hybrids can be constructed using a case-based recommender as one component, and describes a series of experiments in which 20 different hybrids are built and evaluated. Cascade and feature augmentation hybrids are shown to have the highest accuracy over a range of different profile sizes. © Springer-Verlag 2004.