Intelligent service request classification and assignment
View Patent ↗Approaches presented herein enable intelligent service request classification and assignment learning. More specifically, a request comprising a free form text or spoken description is received from a user. The request description is parsed and classified by a regression-based classifier. The regression-based classifier classifies based on, for example: the description itself; the requestor's history of requests, and/or supplemental demographics about a requestor. Optionally, a user may verify the classification or select from a plurality of returned classifications. A service provider or administrator confirms that a classification is correct. If not, the incorrectly classified request is queued. If so, the correctly classified request is added to a set of training data to be used in classifying future requests.
1. A method of automatically processing a service request, comprising:
receiving, at an automated user assistance system, a single description of a service request that is freeform in a natural language from a user;
converting the description and an identification of the user into a set of feature vectors;
applying to the service request description a logistic regression algorithm configured to determine a classification of the service request based on the description and a historic frequency of classified service requests submitted by the user in the set of feature vectors;
automatically routing to the user a service area designated based on the classification to fulfill the service request;
forwarding the service request to automated verification system based on the classification;
receiving a determination whether the service request is correctly classified; and
continuously training the logistic regression algorithm against an increasingly refined set of training data of correctly classified service requests in a memory.
2. The method of claim 1 , wherein the logistic regression algorithm is a naïve Bayes classifier.
3. The method of claim 1 , where, in the case that the service request is correctly classified, the method further comprises storing an identification of the user and a classification of the service request in the set of training data in the memory.
4. The method of claim 3 , further comprising:
calculating a frequency the user requests a service of the classification; and
storing the frequency in the set of training data in the memory.
5. The method of claim 1 , further comprising:
predicting a probability a classification determined with the logistic regression algorithm applies to the service request; and
in the case that the probability is within a threshold, assigning the classification to the service request automatically.
6. The method of claim 5 , where, in the case that the probability is under a threshold, the method further comprises:
returning a set of one or more classification options to the user; and
assigning a classification option selected by the user to the service request.
7. The method of claim 1 , wherein the logistic regression algorithm is further configured to determine a classification of the service request based on supplemental demographics about the user, the supplemental demographics being collected from one or more of: a human resources (HR) system, a configuration management database (CMDB), a Customer Relationship Management (CRM) system, an Enterprise Resource Planning (ERP) system, and a social media system.
8. A computer system for automatically processing a service request, the computer system comprising:
a memory device comprising program instructions;
a bus coupled to the memory device; and
a processor, for executing the program instructions, coupled to a request management tool via the bus that when executing the program instructions causes the system to:
receive, at an automated user assistance system, a single description of a service request that is freeform in a natural language from a user;
converting the description and an identification of the user into a set of feature vectors;
apply to the service request description a logistic regression algorithm configured to determine a classification of the service request based on the description and a historic frequency of classified service requests submitted by the user in the set of feature vectors;
automatically route to the user a service area designated based on the classification to fulfill the service request;
forward the service request to automated verification system based on the classification;
receive a determination whether the service request is correctly classified; and
continuously train the logistic regression algorithm against an increasingly refined set of training data of correctly classified service requests in a memory.
9. The system of claim 8 , wherein the logistic regression algorithm is a naïve Bayes classifier.
10. The system of claim 8 , where, in the case that the service request is correctly classified, the program instructions further cause the system to store an identification of the user and a classification of the service request in the set of training data in the memory.
11. The system of claim 10 , the program instructions further causing the system to:
calculate a frequency the user requests a service of the classification; and
store the frequency in the set of training data in the memory.
12. The system of claim 8 , the program instructions further causing the system to:
predict a probability a classification determined with the logistic regression algorithm applies to the service request; and
in the case that the probability is within a threshold, assign the classification to the service request automatically.
13. The system of claim 12 , where, in the case that the probability is under a threshold, the program instructions further cause the system to:
return a set of one or more classification options to the user; and
assign a classification option selected by the user to the service request.
14. The system of claim 8 , wherein the logistic regression algorithm is further configured to determine a classification of the service request based on supplemental demographics about the user, the supplemental demographics being collected from one or more of: a human resources (HR) system, a configuration management database (CMDB), a Customer Relationship Management (CRM) system, an Enterprise Resource Planning (ERP) system, and a social media system.
15. A computer program product for automatically processing a service request, the computer program product comprising a computer readable storage device, and program instructions stored on the computer readable storage device, to
receive, at an automated user assistance system, a single description of a service request that is freeform in a natural language from a user;
convert the description and an identification of the user into a set of feature vectors;
apply to the service request description a logistic regression algorithm configured to determine a classification of the service request based on the description, a historic frequency of classified service requests submitted by the user, and supplemental demographics about the user in the set of feature vectors;
automatically route to the user a service area designated based on the classification to fulfill the service request;
forward the service request to automated verification system based on the classification;
receive a determination whether the service request is correctly classified; and
continuously train the logistic regression algorithm against an increasingly refined set of training data of correctly classified service requests in a memory.
16. The computer program product of claim 15 , wherein the logistic regression algorithm is a naïve Bayes classifier.
17. The computer program product of claim 15 , where, in the case that the service request is correctly classified, the program instructions are further configured to store an identification of the user and a classification of the service request in the set of training data in the memory.
18. The computer program product of claim 17 , the program instructions being further configured to:
calculate a frequency the user requests a service of the classification; and
store the frequency in the set of training data in the memory.
19. The computer program product of claim 15 , the program instructions being further configured to:
predict a probability a classification determined with the logistic regression algorithm applies to the service request; and
in the case that the probability is within a threshold, assign the classification to the service request automatically.
20. The computer program product of claim 19 , where, in the case that the probability is under a threshold, the program instructions are further configured to:
return a set of one or more classification options to the user; and
assign a classification option selected by the user to the service request.