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Training

Training begins by clearing all statistics from the KB, leaving only its structure, and then the KB populates the concept models of categories using a categorized collection of message texts, called a corpus. A corpus contains your texts for training assigned to categories. When you define the corpus, you specify which email fields you want to train your KB on.

For Siebel Email Response, when you train the corpus, submit emails in the same order that you might receive email on a typical day. Do not process a group of emails for the same category at the same time. Submit the emails in the training corpus in a random sequence.

For Siebel Call Center and Siebel eService, train the KB based on the topics associated with the business objects that will be retrieved and displayed in response to natural language queries from agents.

A corpus should contain examples of all categorized emails, or requests that you expect to receive in your production environment. The number of emails or requests in each category should be in proportion to the number that you receive in your production environment.

Categories in the KB will only return scores (confidence-level percentages) after they have gathered sufficient statistical information.