Improving Naive Bayes accuracy for text classification
Regarding your first question...

Do you anticipate the majority category to be similarly over-represented in real-world data as it is in your training data? If so, perhaps you could perform two-step classification:


Train a binary classifier (on all your training data) to predict membership (yes/no) in the majority class.
Train a multi-class classifier (on the rest of the training data) to predict membership in the remaining minority classes.