Behavioral filter for personalized recommendations
Abstract:
This disclosure describes systems and associated methods that can selectively filter seed behavior, e.g., user activity used to generate item recommendations. In some embodiments, seed behaviors and catalog items are associated with categories in an electronic catalog, and a particular seed behavior is used to generate user recommendations if it is more recent than a user's last purchase in the category of the seed behavior. For example, a user's activity in the TV category, e.g., viewing various TV models, may not be used to generate recommendations if the activity occurred prior to the user's purchase of a TV. As a result, in certain embodiments, additional TVs may not appear in the user's recommendations following her purchase, reflecting that the user has fulfilled her desire to purchase a TV.
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