Recommendation engine based on optimized combination of recommendation algorithms
AssigneeOptimizely, Inc.
InventorEthan Berl
Life of this patent
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Abstract
A method includes receiving a training metric, the training metric indicating a parameter to be optimized by content recommendations. A machine learning algorithm maybe used to determine a plurality of different combinations of the recommendation algorithms in the experiment, and each of one or more of the plurality of combinations may be used to generate a content recommendation for one or more visitors. The statistical performance of each of the one or more combinations in optimizing the parameter (based on the content recommendations generated by those combinations) may be monitored and a higher percentage of visitors may be allocated to a combination that generates content recommendations that are the most effective at optimizing the parameter.
Claims20
A method comprising:
- receiving a training metric, the training metric indicating a parameter to be optimized by a set of recommendation algorithms, the set of recommendation algorithms operating as an experiment for content hosted by a content provider;
- generating, by a processing device, a plurality of different combinations of the recommendation algorithms in the set, each combination comprising a set of weights;
- generating, by each of the plurality of combinations of the recommendation algorithms, a content recommendation for each of one or more users;
- for each of the plurality of combinations, monitoring the performance of the combination in optimizing the parameter based on the one or more content recommendations generated by the combination;
- and
- allocating a portion of new users to a combination generating content recommendations that result in a highest level of optimization of the parameter, wherein subsequent content recommendations generated by the combination optimizing the parameter the most are integrated into a user interface through which the portion of new users interact with the content provider.
A system comprising:
- a memory;
- and
- a processing device operatively coupled to the memory, the processing device to:
- receive a training metric, the training metric indicating a parameter to be optimized by a set of recommendation algorithms, the set of recommendation algorithms operating as an experiment for content hosted by a content provider;
- generate a plurality of different combinations of the recommendation algorithms in the set, each combination comprising a set of weights;
- generate, by each of the plurality of combinations, a content recommendation for each of one or more users;
- for each of the plurality of combinations of the recommendation algorithms, monitor the performance of the combination in optimizing the parameter based on the one or more content recommendations generated by the combination;
- and
- allocate a portion of new users to a combination generating content recommendations that result in a highest level of optimization of the parameter, wherein subsequent content recommendations generated by the combination optimizing the parameter the most are integrated into a user interface through which the portion of new users interact with the content provider.
A non-transitory computer readable medium, having instructions stored thereon which, when executed by a processing device, cause the processing device to:
- receive a training metric, the training metric indicating a parameter to be optimized by a set of recommendation algorithms, the set of recommendation algorithms operating as an experiment for content hosted by a content provider;
- generate, by the processing device, a plurality of different combinations of the recommendation algorithms in the set, each combination comprising a set of weights;
- generate, by each of the plurality of combinations of the recommendation algorithms, a content recommendation for each of one or more users;
- for each of the plurality of combinations of the recommendation algorithms, monitor the performance of the combination in optimizing the parameter based on the one or more content recommendations generated by the combination;
- and
- allocate a portion of new users to a combination generating content recommendations that result in a highest level of optimization of the parameter, wherein subsequent content recommendations generated by the combination optimizing the parameter the most are integrated into a user interface through which the portion of new users interact with the content provider.
Dependencies are inferred from the claim text.