TR2006-036

Induction of Compact Decision Trees for Personalized Recommendation
Citation: Nikovski, D.; Kulev, V., "Induction of Compact Decision Trees for Personalized Recommendation", ACM Symposium on Applied Computing (SAC), April 2006 (SAC 2006)
Date:May 2006
MERL Contact:Daniel Nikovski

We propose a method for induction of compact optimal recommendation policies based on discovery of frequent itemsets in a purchase database, followed by the application of standard decision tree learning algorithms for the purposes of simplification and compaction of the recommendation policies. Experimental results suggest that the structure of such policies can be exploited to partition the space of customer purchasing histories much more efficiently than frequent itemset discovery algorithms alone would allow.

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