Method and apparatus for generating a recommended content list
First Claim
1. A method for generating a content recommendation for a given user of a recommendation system, the method executable at a recommendation server, the method comprising:
- receiving, by the recommendation server, from an electronic device associated with the given user a request for the content recommendation;
responsive to the request generating, by the recommendation server, a set of content recommendations for the given user, the generating being executed by a prediction module of the recommendation server, the prediction module having been trained using a training set of training events, such that for each given training event from the training set of training events;
at least one user-nonspecific feature is used as a first input parameter for the prediction module training, the at least one user-nonspecific feature having been retrieved from the latest version of a snapshot archive available at a time of the given training event occurring, the latest version of the snapshot archive having been generated prior to the time of the given training event occurring;
at least one user-specific feature is used as a second input parameter for the prediction module training the at least one user-specific feature available at the time of the given training event occurring;
the generating comprising;
acquiring at least one in-use user non-specific feature from a then latest version of the snapshot archive, the then latest version of the snapshot archive having been generated prior to the generating the set of content recommendations;
generating an in-use user-specific feature at a moment of time of generating the set of content recommendations;
using the at least one in-use user non-specific feature and the in-use user-specific feature for generating the set of content recommendations;
transmitting at least a sub-set of the set of content recommendations to the electronic device.
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Accused Products
Abstract
There is disclosed a method for generating a content recommendation for a given user of a recommendation system. The method comprises: receiving a request for the content recommendation; responsive to the request generating a set of content recommendations for the given user, the generating being executed by a prediction module of the recommendation server, the prediction module having been trained using a training set of training events, such that for each given training event from the training set of training events: at least one user-nonspecific feature is used as a first input parameter for the prediction module training, the at least one user-nonspecific feature having been retrieved from a latest version of a snapshot archive available at a time of the given training event occurring; and at least one user-specific feature is used as a second input parameter for the prediction module training.
219 Citations
14 Claims
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1. A method for generating a content recommendation for a given user of a recommendation system, the method executable at a recommendation server, the method comprising:
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receiving, by the recommendation server, from an electronic device associated with the given user a request for the content recommendation; responsive to the request generating, by the recommendation server, a set of content recommendations for the given user, the generating being executed by a prediction module of the recommendation server, the prediction module having been trained using a training set of training events, such that for each given training event from the training set of training events; at least one user-nonspecific feature is used as a first input parameter for the prediction module training, the at least one user-nonspecific feature having been retrieved from the latest version of a snapshot archive available at a time of the given training event occurring, the latest version of the snapshot archive having been generated prior to the time of the given training event occurring; at least one user-specific feature is used as a second input parameter for the prediction module training the at least one user-specific feature available at the time of the given training event occurring; the generating comprising; acquiring at least one in-use user non-specific feature from a then latest version of the snapshot archive, the then latest version of the snapshot archive having been generated prior to the generating the set of content recommendations; generating an in-use user-specific feature at a moment of time of generating the set of content recommendations; using the at least one in-use user non-specific feature and the in-use user-specific feature for generating the set of content recommendations; transmitting at least a sub-set of the set of content recommendations to the electronic device. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method of training a prediction module, the prediction module being part of a recommendation server, the method comprising:
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generating a training set of training events, such that for each given training event from the training set of training events; at least one user-nonspecific feature is used as a first input parameter for the prediction module training, the at least one user-nonspecific feature having been generated and stored prior to generating the training set, and retrieved from a latest version of a snapshot archive available at a time of the given training event occurring, the latest version of the snapshot archive having been generated prior to the time of the given training event occurring; at least one user-specific feature is used as a second input parameter for the prediction module training, at least one user-specific feature generated at the time of the given training event occurring; using the training set to train the prediction module to generate an indication of at least one recommendation item. - View Dependent Claims (11, 12, 13)
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14. A server, the server comprising:
a processing module configured to; receive from an electronic device associated with the given user a request for the content recommendation; responsive to the request, generate a set of content recommendations for the given user, the generating being executed by a prediction module of the recommendation server, the prediction module having been trained using a training set of training events, such that for each given training event from the training set of training events; at least one user-nonspecific feature is used as a first input parameter for the prediction module training, the at least one user-nonspecific feature having been retrieved from a latest version of a snapshot archive available at a time of the given training event occurring, the latest version of the snapshot archive having been generated prior to the time of the given training event occurring; at least one user-specific feature is used as a second input parameter for the prediction module training, at least one user-specific feature available at the time of the given training event occurring, the at least one user-specific feature being non-available at the time the latest version of the snapshot archive was generated; the generating comprising; acquiring at least one in-use user non-specific feature from a then latest version of the snapshot archive, the then latest version of the snapshot archive having been generated prior to the generating the set of content recommendations; generating an in-use user-specific feature at a moment of time of generating the set of content recommendations; using the at least one in-use user non-specific feature and the in-use user-specific feature for generating the set of content recommendations; transmit at least a sub-set of the set of content recommendations to the electronic device.
Specification