Abstract
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.
Original language | English |
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Publication date | 2010 |
Number of pages | 5 |
Publication status | Published - 2010 |
Externally published | Yes |
Keywords
- Recommender Systems
- Information Overload
- Contextual Information
- Random Walks
- Contextual Graphs