Movie Recommendation using Random Walks over the Contextual Graph

TY - CONF

T1 - Movie Recommendation using Random Walks over the Contextual Graph

AU - Bogers, Toine

PY - 2010

Y1 - 2010

N2 - Recommender systems have become an essential tool in fighting information overload. However, the majority of recommendation algorithms focus only on using ratings information, while disregarding information about the context of the recommendation process. We present ContextWalk, a recommendation algorithm that makes it easy to include different types of contextual information. It models the browsing process of a user on a movie database website by taking random walks over the contextual graph. We present our approach in this paper and highlight a number of future extensions with additional contextual information.

AB - Recommender systems have become an essential tool in fighting information overload. However, the majority of recommendation algorithms focus only on using ratings information, while disregarding information about the context of the recommendation process. We present ContextWalk, a recommendation algorithm that makes it easy to include different types of contextual information. It models the browsing process of a user on a movie database website by taking random walks over the contextual graph. We present our approach in this paper and highlight a number of future extensions with additional contextual information.

KW - recommender systems

KW - context

KW - random walks

KW - contextual recommendation

KW - movie recommendation

M3 - Paper

T2 - Second Workshop on Context-Aware Recommender Systems

Y2 - 26 September 2010 through 30 September 2010

ER -