Analyzing monitoring system events using natural language processing (NLP)
A language device is described. A language device includes processing circuitry configured to: determine an urgency level of a message based at least in part on a natural language processing (NLP) model; determine a priority of an event associated with the message based at least in part on the urgency level; and order the message relative to a plurality of other messages in a customer queue based at least in part on the priority of the event associated with the message.
1. A language device comprising:
processing circuitry configured to:
determine an urgency level of a message based at least in part on a natural language processing (NLP) model;
determine a priority of an event associated with the message based at least in part on the urgency level; and
order the message relative to a plurality of other messages in a customer queue based at least in part on the priority of the event associated with the message.
2. The language device of claim 1 , wherein the processing circuitry is further configured to:
determine a plurality of NLP models, the NLP model being among the plurality of NLP models and corresponding to a language pattern associated with the message.
3. The language device of claim 1 , wherein the processing circuitry is further configured to:
determine a resolution type based at least in part on the message; and
retrain the NLP model based at least in part on the resolution type.
4. The language device of claim 3 , wherein the processing circuitry is further configured to:
determine an NLP model update based on an event disposition.
5. The language device of claim 1 , wherein the processing circuitry is further configured to:
determine an alert to be transmitted to a first responder based at least in part on the NLP model.
6. The language device of claim 1 , wherein the processing circuitry is further configured to:
determine a plurality of messages associated with the message; and
input the plurality of messages to another NLP model to determine a performance level of an agent associated with at least one of the plurality of messages.
7. The language device of claim 1 , wherein the processing circuitry is further configured to:
determine a plurality of messages associated with the message; and
input the plurality of messages to another NLP model to determine an effectiveness level of an event disposition.
8. The language device of claim 1 , wherein the processing circuitry is further configured to:
input voice data associated with a voice call to another NLP model to prioritize the voice call.
9. The language device of claim 8 , wherein the other NLP model is configured to detect an emotion of a person associated with the voice data.
10. The language device of claim 1 , wherein the language device further comprises a communication interface in communication with the processing circuitry, the communication interface being configured to:
receive the message, the message including information about the event; and
transmit the message to at least one agent device.
11. A method performed by a language device, the method comprising:
determining an urgency level of a message based at least in part on a natural language processing (NLP) model;
determining a priority of an event associated with the message based at least in part on the urgency level; and
ordering the message relative to a plurality of other messages in a customer queue based at least in part on the priority of the event associated with the message.
12. The method of claim 11 , further comprising:
determining a plurality of NLP models, the NLP model being among the plurality of NLP models and corresponding to a language pattern associated with the message.
13. The method of claim 11 , further comprising:
determining a resolution type based at least in part on the message; and
retraining the NLP model based at least in part on the resolution type.
14. The method of claim 13 , further comprising:
determining an NLP model update based on an event disposition.
15. The method of claim 11 , further comprising:
determining an alert to be transmitted to a first responder based at least in part on the NLP model.
16. The method of claim 11 , further comprising:
determining a plurality of messages associated with the message; and
inputting the plurality of messages to another NLP model to determine a performance level of an agent associated with at least one of the plurality of messages.
17. The method of claim 11 , further comprising:
determining a plurality of messages associated with the message; and
inputting the plurality of messages to another NLP model to determine an effectiveness level of an event disposition.
18. The method of claim 11 , further comprising:
inputting voice data associated with a voice call to another NLP model to prioritize the voice call.
19. The method of claim 18 , wherein the other NLP model is configured to detect an emotion of a person associated with the voice data.
20. The method of claim 11 , further comprising:
receiving the message, the message including information about the event; and
transmitting the message to at least one agent device.