Recommendation Systems
First Claim
1. A method for recommendations, comprising the steps of:
- a. obtaining historical data from numerous users'"'"' actions with numerous items,b. offline training with the historical data to calculate recommendation IDs,c. saving the recommendation IDs for more than one item or more than one user, andd. utilizing a recommendation component, which upon a request with a target ID and a client ID, in real-time, looks up the recommendations, and returns the recommendation IDswherein at least one of the steps utilizes a computing device.
2 Assignments
0 Petitions
Accused Products
Abstract
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.
-
Citations
20 Claims
-
1. A method for recommendations, comprising the steps of:
-
a. obtaining historical data from numerous users'"'"' actions with numerous items, b. offline training with the historical data to calculate recommendation IDs, c. saving the recommendation IDs for more than one item or more than one user, and d. utilizing a recommendation component, which upon a request with a target ID and a client ID, in real-time, looks up the recommendations, and returns the recommendation IDs wherein at least one of the steps utilizes a computing device. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
-
-
11. A method of calculating categorical related items, comprising the steps of:
-
a. obtaining historical data from numerous users'"'"' actions with numerous items, and a target items is linked to a target category, b. determining the most related categories to the target category, c. listing the top acted-upon items in each most related category, d. calculating the weight based upon the top acted-upon item number of actions and the related category similarity, and e. determining the categorical related items as the items with the largest weights, wherein at least one of the steps utilizes a computing device. - View Dependent Claims (12, 13, 14, 15, 16)
-
-
17. A method of calculating related categories, comprising the steps of:
-
a. obtaining historical data from numerous users'"'"' actions with numerous items, and each item is linked to at least on category, b. choosing a target category, c. determining the likelihood of acting on items in other category, d. determining the likelihood of acting on items in the target category using self-similarity that depends upon users with multiple actions in said target category, and e. finding the top most related categories to the target category; wherein at least one of the steps utilizes a computing device. - View Dependent Claims (18, 19, 20)
-
Specification