Probabilistic Modeling of Progressive Filtering
  Progressive filtering is a simple way to perform hierarchical classification,
inspired by the behavior that most humans put into practice while attempting to
categorize an item according to an underlying taxonomy. Each node of the
taxonomy being associated with a different category, one may visualize the
categorization process by looking at the item going downwards through all the
nodes that accept it as belonging to the corresponding category. This paper is
aimed at modeling the progressive filtering technique from a probabilistic
perspective, in a hierarchical text categorization setting. As a result, the
designer of a system based on progressive filtering should be facilitated in
the task of devising, training, and testing it.
