1. In a computerized knowledge learning system, a method for configuring knowledge sets and AI algorithms, useful in association with an automated messaging system, the method comprising: receiving at least one training message; selecting a subsection of text from the at least one training message; selecting a knowledge set from a plurality of knowledge sets for the selected subsection of text based upon user, industry, and service type, wherein each knowledge set includes probabilistic associations between a term and a category; selecting an insight from a plurality of insights for the selected subsection of text based upon associations of the terms within the subsection of text given the selected knowledge set; categorizing the training message based upon the insight; receiving one of approval or rejection of the categorization; and updating the probabilistic associations in response to the received approval or rejection to improve classification accuracy.
1. In a computerized knowledge learning system, a method for configuring knowledge sets and AI algorithms, useful in association with an automated messaging system, the method comprising: receiving at least one training message; selecting a subsection of text from the at least one training message; selecting a knowledge set from a plurality of knowledge sets for the selected subsection of text based upon user, industry, and service type, wherein each knowledge set includes probabilistic associations between a term and a category; selecting an insight from a plurality of insights for the selected subsection of text based upon associations of the terms within the subsection of text given the selected knowledge set; categorizing the training message based upon the insight; receiving one of approval or rejection of the categorization; and updating the probabilistic associations in response to the received approval or rejection to improve classification accuracy. 6. The method of claim 1 , further comprising generating a new insight in the plurality of insights.