System and method for item recommendations
First Claim
1. A computerized method for generating a recommendation of an item to an advisee, comprising the steps of:
- receiving a recommendation request comprising a selected item list from an advisee for a recommendation by a recommendation system;
in response to the recommendation request, computing, by a processor, a plurality of similarity factors based on;
at least one advisee profile from at least one rated item and determining which at least one user has already rated the item, wherein the advisee profile comprises a plurality of records, each record including a user identifier, an item identifier, and a rating value, such that each record is linked in a first and a second dimension; and
items from the selected item list that indicate similarity between the advisee and a plurality of users of the recommendation system who have previously provided ratings of items from the selected item list;
selecting, from the plurality of users of the recommendation system, neighboring users to the advisee, according to the similarity factors;
generating a recommendation of at least one item of the selected item list, according to the previously provided ratings of the at least one item by the neighboring users,wherein the similarity factors of the advisee are not calculated with respect to all users for every individual recommendation request.
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Accused Products
Abstract
Means and a computerized method for recommending items such as books and audio compact disks. For each item, a user profile includes ratings provided by users of the system. Unlike present recommendation systems, the user profiles do not include pre-computed similarity factors measuring similarity between users. Rather, when an advisee requests a recommendation, similarity measures are computed comparing the advisee to other users, and the similarity measures are associated with the other users. A subset of the users is selected, where the subset includes the users most similar to the advisee. A recommendation is made based on the ratings by the members of the selected subset.
74 Citations
31 Claims
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1. A computerized method for generating a recommendation of an item to an advisee, comprising the steps of:
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receiving a recommendation request comprising a selected item list from an advisee for a recommendation by a recommendation system; in response to the recommendation request, computing, by a processor, a plurality of similarity factors based on; at least one advisee profile from at least one rated item and determining which at least one user has already rated the item, wherein the advisee profile comprises a plurality of records, each record including a user identifier, an item identifier, and a rating value, such that each record is linked in a first and a second dimension; and items from the selected item list that indicate similarity between the advisee and a plurality of users of the recommendation system who have previously provided ratings of items from the selected item list; selecting, from the plurality of users of the recommendation system, neighboring users to the advisee, according to the similarity factors; generating a recommendation of at least one item of the selected item list, according to the previously provided ratings of the at least one item by the neighboring users, wherein the similarity factors of the advisee are not calculated with respect to all users for every individual recommendation request. - View Dependent Claims (2, 3, 4, 5, 6, 14, 16, 18, 20, 22, 24, 26, 28, 31)
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7. A computerized method for generating a recommendation of an item to an advisee, comprising the steps of:
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receiving a recommendation request comprising a selected item list from an advisee for the recommendation by a recommendation system; in response to the recommendation request, computing, by a processor, a plurality of similarity factors based on at least one advisee profile from at least one rated item and determining which at least one user has already rated the item; selecting a first set of users from a group of users of the recommendation system based on the selected item list; selecting neighboring users from the first set of users based on similarities between the advisee and each member of the first set of users; and generating a recommendation of at least one item from the selected item list based on ratings provided by each neighboring user, wherein the computing comprises determining the similarity factors between the advisee and the neighboring users only for the items of the selected item list. - View Dependent Claims (8, 9, 10, 11, 12, 13, 15, 17, 19, 21, 23, 25, 27, 29)
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30. A computerized method for recommending an item to an advisee utilizing a user profile comprising, for each of a multitude of items, at least a rating value and excluding any pre-computed similarity factor measuring similarity between users, wherein the method constructs a recommendation to the advisee and comprises:
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calculating, by a processor, for use within a recommendation request only, a multitude of similarity factors measuring the similarity between the advisee and the multitude of other users; associating the similarity factors with the other users; determining a subset, from the multitude of users, of neighboring users with the similarity factors nearest in value to the advisee; and recommending at least one item from a selected item list in the recommendation request from the advisee based on the similarity factors of the neighboring users and based on rating values of the items by the neighboring users.
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Specification