Separate feature spaces for document zones.

There are two strategies that can be used for document zones. Above we upweighted words that appear in certain zones. This means that we are using the same features (that is, parameters are across different zones), but we pay more attention to the occurrence of terms in particular zones. An alternative strategy is to have a completely separate set of features and corresponding parameters for words occurring in different zones. This is in principle more powerful: a word could usually indicate the topic Middle East when in the title but Commodities when in the body of a document. But, in practice, tying parameters is usually more successful. Having separate feature sets means having two or more times as many parameters, many of which will be much more sparsely seen in the training data, and hence with worse estimates, whereas upweighting has no bad effects of this sort. Moreover, it is quite uncommon for words to have different preferences when appearing in different zones; it is mainly the strength of their vote that should be adjusted. Nevertheless, ultimately this is a contingent result, depending on the nature and quantity of the training data.