The Effect of Using Hierarchical Classifiers in Text Categorization

Given a set of categories, with or without a preexisting hierarchy among them, we consider the problem of assigning documents to one or more of these categories from the point of view of a hierarchy with more or less depth. We can choose to make use of none, part or all of the hierarchical structure to improve the categorization effectiveness and efficiency. It is possible to create additional hierarchy among the categories. We describe a procedure for generating a hierarchy of classifiers that models the hierarchy structure. We report on computational experience using this procedure. We show that judicious use of a hierarchy can significantly improve both the speed and effectiveness of the categorization process. Using the Reuters-21578 corpus, we obtain an improvement in running time of over a factor of three and a 5% improvement in F-measure.