16. A computer-implemented method for training and testing a knowledge base of a computerized customer relationship management system, comprising: collecting, on one or more computers, corpus items into a corpus; assigning, on the one or more computers, a category from a set of predefined categories to individual corpus items; building, on the one or more computers, a knowledge base of a computerized customer relationship management system by performing natural language and semantic analysis of a first subset of corpus items and thereby deriving semantic and statistical information from the corpus items that are associated with nodes in the knowledge base; testing, on the one or more computers, the knowledge base of the computerized customer relationship management system on a second subset of corpus items by extracting concepts from the corpus items of the second subset, performing statistical pattern matching to generate a set of match scores for each corpus item of the second subset, wherein each match score in the match score set represents a confidence level for classifying each corpus item of the second subset into at least one of the predefined categories using the semantic and statistical information associated with the nodes in the knowledge base of the computerized customer relationship management system; and generating and displaying, on the one or more computers, a report based on results produced by the testing step to a user of the computerized customer relationship management system to gauge performance of the knowledge base, so that appropriate adjustments are made to improve the performance of the knowledge base.
16. A computer-implemented method for training and testing a knowledge base of a computerized customer relationship management system, comprising: collecting, on one or more computers, corpus items into a corpus; assigning, on the one or more computers, a category from a set of predefined categories to individual corpus items; building, on the one or more computers, a knowledge base of a computerized customer relationship management system by performing natural language and semantic analysis of a first subset of corpus items and thereby deriving semantic and statistical information from the corpus items that are associated with nodes in the knowledge base; testing, on the one or more computers, the knowledge base of the computerized customer relationship management system on a second subset of corpus items by extracting concepts from the corpus items of the second subset, performing statistical pattern matching to generate a set of match scores for each corpus item of the second subset, wherein each match score in the match score set represents a confidence level for classifying each corpus item of the second subset into at least one of the predefined categories using the semantic and statistical information associated with the nodes in the knowledge base of the computerized customer relationship management system; and generating and displaying, on the one or more computers, a report based on results produced by the testing step to a user of the computerized customer relationship management system to gauge performance of the knowledge base, so that appropriate adjustments are made to improve the performance of the knowledge base. 24. The method of claim 16 , wherein the step of generating and displaying a report includes generating and displaying a report showing, for each of a plurality of pairs of categories, a percentage of corpus items initially assigned to a first category of the pair of categories that were erroneously classified into a second category of the pair of categories.