1. A computerized text classifier system for classifying text on a computer for electronic communication management in a contact center, comprising: a pre-processor, performed by the computer, configured to analyze 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 identified concepts; a knowledge base, stored in the computer, 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; a statistical engine, performed by the computer, for calculating a set of match scores for the concept model 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.
1. A computerized text classifier system for classifying text on a computer for electronic communication management in a contact center, comprising: a pre-processor, performed by the computer, configured to analyze 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 identified concepts; a knowledge base, stored in the computer, 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; a statistical engine, performed by the computer, for calculating a set of match scores for the concept model 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. 7. The computerized text classifier system of claim 1 , wherein the pre-processor selects a script from a plurality of scripts and executes the selected script to identify concepts.