Integrated service centre support
A curator captures input data corresponding to service tasks from an external source. Further, a browser extension collects intermediate service delivery data for the service tasks from the external source. Subsequently, a learner stores the input data and the intermediate service delivery data as training data. Then, a receiver receives a service request from a client. The service request is indicative of a service task to be performed and information associated with the service task. Further, an advisor processes the service request to generate an intermediate service response. Thereafter, the advisor determines a confidence level associated with the intermediate service response and ascertains whether the confidence level associated with service response is below pre-determined threshold level. If the confidence level is below a pre-determined threshold level, the advisor automatically generates a final service response corresponding to service request based on training data.
1. A system comprising:
a curator to capture input data corresponding to a plurality of service tasks from an external source;
a browser extension, in communication with the curator, the browser extension to collect intermediate service delivery data from the external source;
a learner, in communication with the browser extension, the learner to store the input data and the intermediate service delivery data as training data;
a receiver, in communication with the learner, the receiver to receive a service request from a client, wherein the service request is indicative of a service task to be performed and information associated with the service task; and
an advisor, in communication with the receiver, the advisor to:
process the service request to generate an intermediate service response corresponding to the service request, wherein the intermediate service response is generated as an intermediate recommendation;
determine a confidence level associated with the intermediate service response;
ascertain whether the confidence level associated with the service response is below a pre-determined threshold level; and
on ascertaining that the confidence level is below the pre-determined threshold level, generate a final service response corresponding to the service request based on the training data, wherein the final service response is generated as a final recommendation.
2. The system as claimed in claim 1 , wherein the input data includes question-answers pairs and dialog traces corresponding to each of the plurality of service tasks.
3. The system of claim 1 , wherein the advisor is to determine the confidence level associated with the intermediate service response based on a confusion matrix.
4. The system of claim 1 , wherein the advisor further is to, on ascertaining that the confidence level associated with the service response is above the pre-determined threshold level, finalize the intermediate recommendation based on validation from an external system.
5. The system as claimed in claim 1 , wherein the system is trained with the input data and the intermediate service delivery data using machine learning techniques.
6. A system comprising:
a receiver to receive a service request from a client,
an advisor, in communication with the receiver, the advisor to:
process the service request to generate an intermediate service response corresponding to the service request, wherein the intermediate service response is generated as an intermediate recommendation;
determine a confidence level associated with the intermediate service response;
ascertain whether the confidence level associated with the service response is below a pre-determined threshold level;
on ascertaining that the confidence level is below the pre-determined threshold level, extract training data from a database, wherein the training data corresponds to the service request; and
automatically generate a final service response corresponding to the service request based on the training data, wherein the final service response is generated as a final recommendation.
7. The system of claim 6 , wherein the service request is indicative of a service task to be performed and information associated with the service task.
8. The system of claim 6 , wherein the advisor determines the confidence level associated with the intermediate service response based on a confusion matrix.
9. The system of claim 6 , wherein the training data is indicative of data gathered from external sources.
10. The system of claim 6 , wherein the advisor further is to, on ascertaining that the confidence level associated with the service response is above the pre-determined threshold level, finalize the intermediate recommendation based on validation from an external system.
11. The system of claim 6 , wherein the system further comprises:
a curator to capture input data corresponding to a plurality of service tasks from an external source;
a browser extension, in communication with the curator, the browser extension to collect intermediate service delivery data from the external source; and
a learner, in communication with the browser extension, the learner to store the input data and the intermediate service delivery data as the training data.
12. The system as claimed in claim 11 , wherein the input data includes question-answers pairs and dialog traces corresponding to each of the plurality of service tasks.
13. The system as claimed in claim 6 , wherein the system is trained with the training data using machine learning techniques.
14. A computer-implemented method, executed by at least one processor, the method comprising:
receiving a service request from a client,
processing the service request to generate an intermediate service response corresponding to the service request, wherein the intermediate service response is generated as an intermediate recommendation;
determining a confidence level associated with the intermediate service response;
ascertaining whether the confidence level associated with the service response is below a pre-determined threshold level;
on ascertaining that the confidence level is below the pre-determined threshold level, extract training data from a database, wherein the training data corresponds to the service request; and
automatically generate a final service response corresponding to the service request based on the training data, wherein the final service response is generated as a final recommendation.
15. The computer-implemented method of claim 14 , wherein the service request is indicative of a service task to be performed and information associated with the service task.
16. The computer-implemented method of claim 14 , wherein the confidence level associated with the intermediate service response based on a confusion matrix.
17. The computer-implemented method of claim 14 , wherein the training data is indicative of data gathered from external sources.
18. The computer-implemented method of claim 14 , wherein the on ascertaining that the confidence level associated with the service response is above the pre-determined threshold level, the intermediate recommendation is finalized based on validation from an external system.
19. The computer-implemented method of claim 14 further comprising:
capturing input data corresponding to a plurality of service tasks from an external source;
collecting intermediate service delivery data from the external source; and
storing the input data and the intermediate service delivery data as the training data.
20. The computer-implemented method of claim 19 , wherein the input data includes question-answers pairs and dialog traces corresponding to each of the plurality of service tasks.