Since a multi-dimensional model can be converted to flat and hierarchical models, three classification strategies are possible, i.e., classifying directly based on the multi-dimensional model and classifying with the equivalent flat or hierarchical models.
two parameters involved are the definition of similarity and the number k. While the standard similarity is defined as tf×idf, a variant (0.5+0.5tf/tf max )×idf that performed better in our preliminary experiments, is applied in this work.