| 摘要 |
This invention deals with recommendation systems. The first embodiment is an off-the-shelf recommendation system is described, where it is easy to integrate with the website database and uses a web service for recommendations, as well as easy to integrate with email. The system receives client ID, item ID and user ID, and returns recommended item IDs. The recommendations include similar items, related items, related users, items likely to be acted upon by a given user (labeled likely items), and users likely to act upon an item (labeled likely users). The recommendations include categorical training, where recommended items are based upon similar categories, where the category types include as product type and brand. The recommendations include similar-to-related training, where similar items are used to find related items. These two intelligent methods work for items with no, few or numerous actions.
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