Hybrid Systems for Personalized Recommendations

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A contextual-bandit approach to personalized news article recommendation (2010, methodology): “Hybrid approaches [11] have been developed by combining two or more recommendation techniques; for example, the inabil ity of collaborative filtering to recommend new items is commonly a lleviated by combining it with content-based filtering.”
Online Clustering of Bandits (2014, background): “Examples of the second approach are the more traditional collaborative-filtering (e.g., (Schafer et al., 1999)), content-based filtering, and hybrid approaches (e.g. (Burke, 2005)).”
Personalized recommendation on dynamic content using predictive bilinear models (2009, methodology): “Since the estimated CTR of an item at time t, denoted by CTRj,t, provides tremendous insight on the quality of the item at time t, we followed the hybrid approaches [10] to combine CTR with the score from the content-based approach.”
Data Mining for Web Personalization (2007, background): “A detailed examination of different approaches to create hybrid recommender systems is presented in [21] (see also Chapter 12 of this book [22]).”
SCENE: a scalable two-stage personalized news recommendation system (2011, background): “Representative examples include [4, 5], in which the inability of collaborative ﬁltering to recommend news items is commonly alleviated by combining it with content-based ﬁltering.”