NETWORK DEVICE PREDICTIVE MODELING

• US 20160171374A1
• Filed: 03/26/2015
• Published: 06/16/2016
• Est. Priority Date: 12/10/2014
• Status: Active Grant

• Current Assignee: Belkin International Incorporated (Hon Hai Precision Industry Co., Ltd.)
• Original Assignee: Belkin International Incorporated (Hon Hai Precision Industry Co., Ltd.)
• Inventors: Kim, Ryan Yong
• Granted Patent: US 10,460,243 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 2219/2642 Domotique, domestic, home control, automation, smart house
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: H04L 43/16 Threshold monitoring
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46

Abstract

Techniques and systems are provided for predictive modeling based on interactions with a network device. For example, a method may include generating a prediction including a correlation between an interaction with a network device and a context, wherein the interaction is associated with a function performed by the network device. Confidence parameters associated with the prediction can be determined. The prediction can be tested by analyzing received interaction data and contextual data, and the analysis can include determining whether the interaction with the network device occurred in the correlated context. A confidence value can be calculated based on the testing outcome, and can be compared to the confidence parameters. A message relating to modification of the confidence parameters can be transmitted.

Claims

1. A computer-implemented method, comprising:

generating, at a computing device, a prediction including a correlation between an interaction with a network device and a context, wherein the interaction is associated with a function performed by the network device;

determining confidence parameters associated with the prediction;

testing the prediction, wherein testing includes analyzing received interaction data and contextual data, and wherein analyzing includes determining whether the interaction with the network device occurred in the correlated context;

calculating a confidence value based on the testing outcome;

comparing the confidence value to the confidence parameters; and

transmitting a message, wherein the message relates to a modification of the confidence parameters.

2. The computer-implemented method of claim 1, wherein the confidence parameters include a threshold confidence value and a threshold number of observations, wherein the observations correspond to the correlated context occurring.

3. The computer-implemented method of claim 2, wherein comparing the confidence value to the confidence parameters includes determining whether the confidence value has reached the threshold confidence value and determining whether the threshold number of observations has been reached.

4. The computer-implemented method of claim 1, wherein the message is transmitted as part of an initial setup process.

5. The computer-implemented method of claim 1, wherein the message is transmitted in response to determining that the confidence value has not reached a threshold confidence value.

6. The computer-implemented method of claim 1, wherein the message is transmitted in response to:

determining that the confidence value has been reached; and

determining that the threshold number of observations has not been reached.

7. The computer-implemented method of claim 1, further comprising:

receiving input corresponding to an instruction to modify the confidence parameters; and

modifying the confidence parameters.

8. The computer-implemented method of claim 7, wherein modifying the confidence parameters includes transitioning from an initial operational mode to a new operational mode.

9. The computer-implemented method of claim 1, wherein the computing device is the network device, a user device, or a cloud-based device.

10. The computer-implemented method of claim 1, wherein the message further relates to a modification of confidence parameters associated with different prediction, wherein the different prediction includes a correlation between an interaction with a different network device and a different context.

11. A system, comprising:

one or more data processors; and

a non-transitory computer-readable storage medium containing instructions which when executed on the one or more data processors, cause the one or more data processors to perform operations including;

generating a prediction including a correlation between an interaction with a network device and a context, wherein the interaction is associated with a function performed by the network device;

determining confidence parameters associated with the prediction;

testing the prediction, wherein testing includes analyzing received interaction data and contextual data, and wherein analyzing includes determining whether the interaction with the network device occurred in the correlated context;

calculating a confidence value based on the testing outcome;

comparing the confidence value to the confidence parameters; and

transmitting a message, wherein the message relates to a modification of the confidence parameters.

12. The system of claim 11, wherein the confidence parameters include a threshold confidence value and a threshold number of observations, wherein the observations correspond to the correlated context occurring.

13. The system of claim 12, wherein comparing the confidence value to the confidence parameters includes determining whether the confidence value has reached the threshold confidence value and determining whether the threshold number of observations has been reached.

14. The system of claim 11, wherein the message is transmitted as part of an initial setup process.

15. The system of claim 11, wherein the message is transmitted in response to determining that the confidence value has not reached a threshold confidence value.

16. The system of claim 11, wherein the message is transmitted in response to:

determining that the confidence value has been reached; and

determining that the threshold number of observations has not been reached.

17. The system of claim 11, wherein the operations further include:

receiving input corresponding to an instruction to modify the confidence parameters; and

modifying the confidence parameters.

18. The system of claim 17, wherein modifying the confidence parameters includes transitioning from an initial operational mode to a new operational mode.

19. The system of claim 11, wherein the computing device is the network device, a user device, or a cloud-based device.

20. The system of claim 11, wherein the message further relates to a modification of confidence parameters associated with different prediction, wherein the different prediction includes a correlation between an interaction with a different network device and a different context.

21. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause a data processing apparatus to:

generate a prediction including a correlation between an interaction with a network device and a context, wherein the interaction is associated with a function performed by the network device;

determine confidence parameters associated with the prediction;

test the prediction, wherein testing includes analyzing received interaction data and contextual data, and wherein analyzing includes determining whether the interaction with the network device occurred in the correlated context;

calculate a confidence value based on the testing outcome;

compare the confidence value to the confidence parameters; and

transmit a message, wherein the message relates to a modification of the confidence parameters.

22. The computer-program product of claim 21, wherein the confidence parameters include a threshold confidence value and a threshold number of observations, wherein the observations correspond to the correlated context occurring.

23. The computer-program product of claim 22, wherein comparing the confidence value to the confidence parameters includes determining whether the confidence value has reached the threshold confidence value and determining whether the threshold number of observations has been reached.

24. The computer-program product of claim 21, wherein the message is transmitted as part of an initial setup process.

25. The computer-program product of claim 21, wherein the message is transmitted in response to determining that the confidence value has not reached a threshold confidence value.

26. The computer-program product of claim 21, wherein the message is transmitted in response to:

determining that the confidence value has been reached; and

determining that the threshold number of observations has not been reached.

27. The computer-program product of claim 21, wherein the instructions are further configured to cause the data processing apparatus to:

receive input corresponding to an instruction to modify the confidence parameters; and

modify the confidence parameters.

28. The computer-program product of claim 27, wherein modifying the confidence parameters includes transitioning from an initial operational mode to a new operational mode.

29. The computer-program product of claim 21, wherein the computing device is the network device, a user device, or a cloud-based device.

30. The computer-program product of claim 21, wherein the message further relates to a modification of confidence parameters associated with different prediction, wherein the different prediction includes a correlation between an interaction with a different network device and a different context.