1. A method comprising: accessing a category structure, the category structure including a plurality of categories for items; accessing a set of training data from a plurality of listings from at least one of supply data or demand data, the supply data generated from seller activity of a plurality of users in a networked system, the demand data generated from buyer activity of the plurality of users in the networked system, each listing including a category from the category structure; and providing the set of training data to a categorization application for training, the categorization application capable of building listing statistics by applying a classifier to the set of training data and recommending a category from the category structure for a new listing by utilizing the listing statistics.
1. A method comprising: accessing a category structure, the category structure including a plurality of categories for items; accessing a set of training data from a plurality of listings from at least one of supply data or demand data, the supply data generated from seller activity of a plurality of users in a networked system, the demand data generated from buyer activity of the plurality of users in the networked system, each listing including a category from the category structure; and providing the set of training data to a categorization application for training, the categorization application capable of building listing statistics by applying a classifier to the set of training data and recommending a category from the category structure for a new listing by utilizing the listing statistics. 2. The method of claim 1 , wherein the classifier is a Bayesian classifier.