PROBABILISTIC FRAMEWORK FOR DETERMINING DEVICE ASSOCIATIONS
First Claim
1. A method for device association, comprising:
- receiving, from a database, a plurality of device characteristics corresponding to a plurality of devices, wherein each device of the plurality of devices is associated with a respective set of device characteristics of the plurality of device characteristics;
receiving connection information for the plurality of devices;
performing a machine-learning process based at least in part on the plurality of device characteristics and the connection information;
determining a probability density function for device association based at least in part on an output of the machine-learning process;
identifying a plurality of sets of associated devices based at least in part on the probability density function for device association; and
transmitting, to a device, information for display corresponding to at least one set of the identified plurality of sets of associated devices.
2 Assignments
0 Petitions
Accused Products
Abstract
Methods, systems, and devices for determining device associations are described. Some database systems may store information related to device characteristics. Each of these devices may be operated by one or more users, and each user may operate one or more devices. In some cases, information about users may be more valuable than information about devices. As such, a system may determine probable associations between devices, where an association can correspond to operation by a same user. To determine device associations, the system may perform a machine-learning process (e.g., using probabilistic soft logic (PSL) and a hinge-loss Markov Random Field (HL-MRF) model) on input device characteristics and connection information to generate a probability density function. The probability density function may indicate associations between devices within the system. Based on one or more thresholds, the system may determine sets of associated devices and may transmit this association information for analysis or display.
6 Citations
20 Claims
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1. A method for device association, comprising:
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receiving, from a database, a plurality of device characteristics corresponding to a plurality of devices, wherein each device of the plurality of devices is associated with a respective set of device characteristics of the plurality of device characteristics; receiving connection information for the plurality of devices; performing a machine-learning process based at least in part on the plurality of device characteristics and the connection information; determining a probability density function for device association based at least in part on an output of the machine-learning process; identifying a plurality of sets of associated devices based at least in part on the probability density function for device association; and transmitting, to a device, information for display corresponding to at least one set of the identified plurality of sets of associated devices. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. An apparatus for device association, comprising:
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a processor; memory in electronic communication with the processor; and instructions stored in the memory and executable by the processor to cause the apparatus to; receive, from a database, a plurality of device characteristics corresponding to a plurality of devices, wherein each device of the plurality of devices is associated with a respective set of device characteristics of the plurality of device characteristics; receive connection information for the plurality of devices; perform a machine-learning process based at least in part on the plurality of device characteristics and the connection information; determine a probability density function for device association based at least in part on an output of the machine-learning process; identify a plurality of sets of associated devices based at least in part on the probability density function for device association; and transmit, to a device, information for display corresponding to at least one set of the identified plurality of sets of associated devices. - View Dependent Claims (17, 18, 19)
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20. A non-transitory computer-readable medium storing code for device association, the code comprising instructions executable by a processor to:
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receive, from a database, a plurality of device characteristics corresponding to a plurality of devices, wherein each device of the plurality of devices is associated with a respective set of device characteristics of the plurality of device characteristics; receive connection information for the plurality of devices; perform a machine-learning process based at least in part on the plurality of device characteristics and the connection information; determine a probability density function for device association based at least in part on an output of the machine-learning process; identify a plurality of sets of associated devices based at least in part on the probability density function for device association; and transmit, to a device, information for display corresponding to at least one set of the identified plurality of sets of associated devices.
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Specification