APPROACH FOR ESTIMATING USER RATINGS OF ITEMS
First Claim
1. A method for estimating how a particular user of a plurality of users would rate a particular item of a plurality of items, the method comprising:
- maintaining ratings data that represents ratings given to a plurality of items by a plurality of users, wherein the ratings data indicates that a particular user of the plurality of users has not yet given a rating to a particular item of the plurality of items;
identifying, from the plurality of items, one or more reference items that have been given ratings similar to ratings given to the particular item that the particular user has not yet rated;
identifying one or more other users of the plurality of users that have given ratings to the one or more reference items that are substantially similar to ratings given by the particular user to the one or more reference items;
generating an estimation of how the particular user would rate the particular item based upon ratings given to the particular item by the one or more other users;
wherein the method is performed by one or more computing devices.
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Abstract
According to an embodiment of the invention, an approach is provided for estimating how a particular user would rate a particular item from a plurality of items. The approach is applicable to any type of items, including rental items such as movies, music and games, and the invention is not limited to any particular type of item. One or more items from the plurality of items that have ratings similar to the particular item are identified. One or more other users are identified that have given ratings to the one or more items that are substantially similar to ratings given by the particular user to the one or more items. An estimation is made of how the particular user would rate the particular item based upon ratings for the particular item given by the one or more other users.
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Citations
26 Claims
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1. A method for estimating how a particular user of a plurality of users would rate a particular item of a plurality of items, the method comprising:
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maintaining ratings data that represents ratings given to a plurality of items by a plurality of users, wherein the ratings data indicates that a particular user of the plurality of users has not yet given a rating to a particular item of the plurality of items; identifying, from the plurality of items, one or more reference items that have been given ratings similar to ratings given to the particular item that the particular user has not yet rated; identifying one or more other users of the plurality of users that have given ratings to the one or more reference items that are substantially similar to ratings given by the particular user to the one or more reference items; generating an estimation of how the particular user would rate the particular item based upon ratings given to the particular item by the one or more other users; wherein the method is performed by one or more computing devices. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A computer-readable storage medium storing instructions for estimating how a particular user of a plurality of users would rate a particular item of a plurality of items, the instructions, when executed by one or more computing devices, cause the one or more computing devices to perform:
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maintaining ratings data that represents ratings given to a plurality of items by a plurality of users, wherein the ratings data indicates that a particular user of the plurality of users has not yet given a rating to a particular item of the plurality of items; identifying, from the plurality of items, one or more reference items that have been given ratings similar to ratings given to the particular item that the particular user has not yet rated; identifying one or more other users of the plurality of users that have given ratings to the one or more reference items that are substantially similar to ratings given by the particular user to the one or more reference items; generating an estimation of how the particular user would rate the particular item based upon ratings given to the particular item by the one or more other users; wherein the method is performed by one or more computing devices. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. A method for estimating how a particular user of a plurality of users would rate a particular item of a plurality of items, the method comprising:
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maintaining ratings data that represents ratings given to a plurality of items by a plurality of users, wherein the ratings data indicates that a particular user of the plurality of users has not yet given a rating to a particular item of the plurality of items; identifying, from the plurality of items, one or more similar items that are similar to the particular item; identifying one or more other users of the plurality of users that have given ratings to the one or more similar items that are substantially similar to ratings given by the particular user to the one or more similar items; generating an estimation of how the particular user would rate the particular item based upon ratings given to the particular item by the one or more other users; wherein identifying, from the plurality of items, one or more similar items that are similar to the particular item comprises; associating semantic feature values with the plurality of items, wherein the semantic feature values are classified according to one or more semantic feature value types, wherein each feature value type is associated with a match score; generating a similarly score for a candidate item of the plurality of items based on at least one match score and a number of matches between semantic feature values associated with the candidate item and semantic feature values associated with the particular item; wherein the method is performed by one or more computing devices. - View Dependent Claims (22, 23, 25)
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24. A computer-readable storage medium storing instructions for estimating how a particular user of a plurality of users would rate a particular item of a plurality of items, the instructions, when executed by one or more computing devices, cause the one or more computing devices to perform:
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maintaining ratings data that represents ratings given to a plurality of items by a plurality of users, wherein the ratings data indicates that a particular user of the plurality of users has not yet given a rating to a particular item of the plurality of items; identifying, from the plurality of items, one or more similar items that are similar to the particular item; identifying one or more other users of the plurality of users that have given ratings to the one or more similar items that are substantially similar to ratings given by the particular user to the one or more similar items; generating an estimation of how the particular user would rate the particular item based upon ratings given to the particular item by the one or more other users; wherein identifying, from the plurality of items, one or more similar items that are similar to the particular item comprises; associating semantic feature values with the plurality of items, wherein the semantic feature values are classified according to one or more semantic feature value types, wherein each feature value type is associated with a match score; generating a similarly score for a candidate item of the plurality of items based on at least one match score and a number of matches between semantic feature values associated with the candidate item and semantic feature values associated with the particular item. - View Dependent Claims (26)
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Specification