2010 DataMiningMethodsforRecommender

• (Amatriain et al., 2010) ⇒ Xavier Amatriain, Alejandro Jaimes, Nuria Oliver, and Josep Pujol. (2010). “Data Mining Methods for Recommender Systems.” In: Recommender Systems Handbook.

Subject Headings: Data-Driven Item Recommendation Algorithm

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• http://scholar.google.com/scholar?q=%222010%22+Data+Mining+Methods+for+Recommender+Systems

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Abstract

In this chapter, we give an overview of the main Data Mining techniques used in the context of Recommender Systems. We first describe common preprocessing methods such as sampling or dimensionality reduction. Next, we review the most important classification techniques, including Bayesian Networks and Support Vector Machines. We describe the k-means clustering algorithm and discuss several alternatives. We also present association rules and related algorithms for an efficient training process. In addition to introducing these techniques, we survey their uses in Recommender Systems and present cases where they have been successfully applied.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2010 DataMiningMethodsforRecommender	Nuria Oliver Alejandro Jaimes Xavier Amatriain Josep Pujol			Data Mining Methods for Recommender Systems						2010