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US 10,650,325 B2Granted
Deterministic message distribution
AssigneeMicrosoft Technology Licensing, LLC
InventorsRupesh Gupta, Hsiao-Ping Tseng, Ravi Kiran Holur Vijay, Romer E. Rosales
Life of this patent
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Abstract
This disclosure relates to systems and methods that include configuring a machine learning system to train on a plurality of messages, the machine learning system to output an expected number of positive responses and an expected number of negative responses based on an input message, determining a threshold differential and a weight value using responses to the plurality of messages, and sending the input message in response to a differential between the expected number of positive responses and the weight multiplied by the expected number of negative responses being above the threshold differential.
Claims17
A system comprising:
- a non-transitory machine-readable medium having instructions stored thereon, which, when executed by a processor, cause the system to:
- configure a machine learning system to train on a plurality of training messages, wherein each individual instance of each training message has previously been sent to a first plurality of members of the online system, and each individual instance of each training message indicates one of a plurality of channels by which the individual instance of the training message was sent, and each individual instance of each training message is associated with one of either a positive response, negative response, or no response, from each member to whom the individual instance of the training message was sent, the machine learning system, subsequent to being trained and upon receiving an input message, to output an expected number of positive responses and an expected number of negative responses to be received from a second plurality of members, for each channel of the plurality of channels, based on the input message;
- for the input message targeted for distribution to the second plurality of members of the online system, using the trained machine learning system to generate output indicating a number of positive responses expected from the second plurality of members and a number of negative responses expected from the second plurality of members, for each channel of the plurality of channels;
- calculate, for each channel of the plurality of channels for the input message, a differential value by subtracting from the number of positive responses expected from the second plurality of members, the number of negative responses expected from the second plurality of members, the number of negative responses multiplied by a weighting factor prior to said subtracting;
- select a channel for the input message that results in a highest differential value of the differential values calculated for the input message;
- and
- send the input message to the second plurality of members via the selected channel in response to the highest differential value exceeding a threshold differential value.
4 more elements
A method comprising:
- configuring a machine learning system to train on a plurality of training messages, wherein each individual instance of each training message has previously been sent to a first plurality of members of the online system, each individual instance of each training message indicates one of a plurality of channels by which the instance of the training message was sent, and each individual instance of each training message is associated with one of either a positive response, negative response, or no response, from the member to whom the individual instance of the training message was sent, the machine learning system, subsequent to being trained and upon receiving an input message, to output an expected number of positive responses and an expected number of negative responses to be received from a second plurality of members, for each channel of the plurality of channels, based on the input message;
- for the input message targeted for distribution to the second plurality of members of the online system, using the trained machine learning system, generating output indicating a number of positive responses expected from the second plurality of members and a number of negative responses expected from the second plurality of members, if the input message is sent to the second plurality of members, for each channel of the plurality of channels;
- calculating, for each channel of the plurality of channels for the input message, a differential value by subtracting from the number of positive responses expected from the second plurality of members, the number of negative responses expected from the second plurality of members, the number of negative responses multiplied by a weighting factor prior to said subtracting;
- selecting a channel for the input message that results in a highest differential value of the differential values calculated for the input message;
- and
- sending the input message to the second plurality of members via the selected channel in response to the highest differential value exceeding a threshold differential value.
3 more elements
A non-transitory machine-readable medium having instructions stored thereon, which, when executed by a processor, cause a system to:
- configure a machine learning system to train on a plurality of training messages, wherein each individual instance of each training message has previously been sent to a first plurality of members of the online system, and each individual instance of each training message indicates one of a plurality of channels by which the individual instance of the training message was sent, and each individual instance of each training message is associated with one of either a positive response, negative response, or no response, from the member to whom the individual instance of the training message was sent, the machine learning system, subsequent to being trained and upon receiving an input message, to output an expected number of positive responses and an expected number of negative responses to be received from a second plurality of members, for each channel of the plurality of channels, based on the input message;
- for the input message targeted for distribution to the second plurality of members of the online system, using the trained machine learning system, generating output indicating a number of positive responses expected from the second plurality of members and a number of negative responses expected from the second plurality of members, if the input message is sent to the second plurality of members, for each channel of the plurality of channels, and
- calculating, for each channel of the plurality of channels for the input message, a differential value by subtracting from the number of positive responses expected from the second plurality of members, the number of negative responses expected from the second plurality of members, the number of negative responses multiplied by a weighting factor prior to said subtracting;
- selecting a channel for the input message that results in a highest differential value of the differential values calculated for the input message;
- and
- send the input message to the second plurality of members via the selected channel in response to the highest differential value exceeding a threshold differential value.
3 more elements
Dependencies are inferred from the claim text.