Native machine learning service for user adaptation on a mobile platform
First Claim
1. A method, comprising:
- receiving data related to a plurality of features by a machine-learning service executing on a mobile platform, wherein the received data comprises a called party of a telephone call to be originated by the mobile platform;
determining at least one feature in the plurality of features based on the received data using the machine-learning service;
generating an output by the machine-learning service performing a machine-learning operation on the at least one feature of the plurality of features, wherein the machine-learning operation is selected from among;
an operation of ranking the at least one feature, an operation of classifying the at least one feature, an operation of predicting the at least one feature, and an operation of clustering the at least one feature, wherein the output comprises a prediction of a volume setting and/or a mute setting of the mobile platform; and
sending the output from the machine-learning service.
2 Assignments
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Accused Products
Abstract
Disclosed are apparatus and methods for providing machine-learning services. A machine-learning service executing on a mobile platform can receive data related to a plurality of features. In some cases, the received data can include data related to features received from an application and data related to features received from the mobile platform. The machine-learning service can determine at least one feature based on the received data. The machine-learning service can generate an output by performing a machine-learning operation on the at least one feature. The machine-learning operation can be selected from among an operation of ranking the at least one feature, an operation of classifying the at least one feature, an operation of predicting the at least one feature, and an operation of clustering the at least one feature. The machine-learning service can send the output.
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Citations
30 Claims
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1. A method, comprising:
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receiving data related to a plurality of features by a machine-learning service executing on a mobile platform, wherein the received data comprises a called party of a telephone call to be originated by the mobile platform; determining at least one feature in the plurality of features based on the received data using the machine-learning service; generating an output by the machine-learning service performing a machine-learning operation on the at least one feature of the plurality of features, wherein the machine-learning operation is selected from among;
an operation of ranking the at least one feature, an operation of classifying the at least one feature, an operation of predicting the at least one feature, and an operation of clustering the at least one feature, wherein the output comprises a prediction of a volume setting and/or a mute setting of the mobile platform; andsending the output from the machine-learning service. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A method, comprising:
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receiving feature-related data by a machine-learning service executing on a mobile platform, wherein the feature-related data comprises data related to a called party of a telephone call to be originated by the mobile platform and data related to a second plurality of features received from the mobile platform, and wherein the called party of the telephone call to be originated by the mobile platform and the second plurality of features differ; determining, using the machine-learning service, at least one feature from among the called party of the telephone call to be originated by the mobile platform and the second plurality of features based on the feature-related data; generating an output by the machine-learning service performing a machine-learning operation on the at least one feature, wherein the output comprises a prediction of a volume setting and/or a mute setting of the mobile platform; and sending the output from the machine-learning service to the application. - View Dependent Claims (14, 15)
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16. An article of manufacture including a non-transitory computer-readable storage medium having instructions stored thereon that, when executed by a processor, cause the processor to perform functions comprising:
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receiving data related to a plurality of features, wherein the received data comprises data related to called parties of telephone calls originated by the mobile platform; determining at least one feature in the plurality of features based on the received data; generating an output by performing a machine-learning operation on the at least one feature of the plurality of features, wherein the machine-learning operation is selected from among;
an operation of ranking the at least one feature, an operation of classifying the at least one feature, an operation of predicting the at least one feature, and an operation of clustering the at least one feature, wherein the output comprises a prediction of a volume setting and/or a mute setting of the mobile platform; andsending the output. - View Dependent Claims (17, 18, 19, 20, 21, 22)
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23. A mobile platform, comprising:
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a processor; and a non-transitory computer-readable storage medium configured to store instructions that, when executed by the processor, cause the mobile platform to perform functions comprising; receiving data related to a plurality of features wherein the received data comprises data related to called parties of telephone calls originated by the mobile platform, determining at least one feature in the plurality of features based on the received data; generating an output by performing a machine-learning operation on the at least one feature of the plurality of features, wherein the machine-learning operation is selected from among;
an operation of ranking the at least one feature, an operation of classifying the at least one feature, an operation of predicting the at least one feature, and an operation of clustering the at least one feature, wherein the output comprises a prediction of a volume setting and/or a mute setting of the mobile platform; andsending the output. - View Dependent Claims (24, 25, 26, 27, 28, 29, 30)
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Specification