13. A computer program product storing one or more computer-readable instructions executed by a computer that results in the computer performing a method of classifying text on the computer for electronic communication management in a contact center, the method comprising steps of: analyzing, in the computer, text from an electronic communication received from a customer to determine the customer's intent by identifying concepts in the text and building a concept model containing the concepts; providing, in the computer, a knowledge base having a plurality of nodes including a set of learning nodes, each of the learning nodes being provided with statistical information for determining a relevance of the text to a category associated with the node; calculating, in the computer, a set of match scores for the concept model by using the knowledge base, each match score of the set of match scores indicating the relevance of the text to a category associated with a node of the knowledge base, the category including at least one suggested action to be performed in response to the electronic communication, wherein the suggested action is representative of the relevance of the text to the category, and the suggested action includes generating an automatic response to the customer or routing the electronic communication to an agent to generate an assisted response to the customer; and performing, in the computer, the suggested action in response to the electronic communication based on the calculated set of match scores, in order to improve the response of the contact center to the electronic communications received from customers by the contact center.
13. A computer program product storing one or more computer-readable instructions executed by a computer that results in the computer performing a method of classifying text on the computer for electronic communication management in a contact center, the method comprising steps of: analyzing, in the computer, text from an electronic communication received from a customer to determine the customer's intent by identifying concepts in the text and building a concept model containing the concepts; providing, in the computer, a knowledge base having a plurality of nodes including a set of learning nodes, each of the learning nodes being provided with statistical information for determining a relevance of the text to a category associated with the node; calculating, in the computer, a set of match scores for the concept model by using the knowledge base, each match score of the set of match scores indicating the relevance of the text to a category associated with a node of the knowledge base, the category including at least one suggested action to be performed in response to the electronic communication, wherein the suggested action is representative of the relevance of the text to the category, and the suggested action includes generating an automatic response to the customer or routing the electronic communication to an agent to generate an assisted response to the customer; and performing, in the computer, the suggested action in response to the electronic communication based on the calculated set of match scores, in order to improve the response of the contact center to the electronic communications received from customers by the contact center. 19. The computer program product of claim 13 , further comprising a step of selecting an appropriate script from a plurality of scripts and executing the selected script to identify concepts in the text.